diff --git a/.gitignore b/.gitignore index 7bf42561d7a277cd5e24d9a6a9839fc01e917321..7074e9757018713aabd60e0ea9be4e85483399e2 100644 --- a/.gitignore +++ b/.gitignore @@ -2,4 +2,8 @@ .RData .Rhistory analysis_and_scripts/.ipynb_checkpoints -sources_ignored \ No newline at end of file +sources_ignored +Kandi.aux +Kandi.log +Kandi.out +Kandi.toc diff --git a/Kandi.pdf b/Kandi.pdf index 9503544e2ea040eea14b49af9f64e0b8cae65e8c..c69527cea1e8fa863a0ea0b985cb9fc7076b361a 100644 Binary files a/Kandi.pdf and b/Kandi.pdf differ diff --git a/Kandi.synctex.gz b/Kandi.synctex.gz index 3df2b871e8bb736662453ec4008bb27649947107..4ef303910ba93a886fe7dbb7f85a9e0b35fd9ba2 100644 Binary files a/Kandi.synctex.gz and b/Kandi.synctex.gz differ diff --git a/Kandi.tex b/Kandi.tex index 0cdc83828db43f4f23d88667b12a760154db72a0..ede30a23db80ca62ec8f235060d6efdbb2436281 100644 --- a/Kandi.tex +++ b/Kandi.tex @@ -403,15 +403,13 @@ Joukko $\s$ katkaisee (blocks) polun $p$, jos vähintään toinen seuraavista eh \end{maar} - - \begin{maar}[Takaovikriteeri (\emph{back-door criterion}) \cite{pearl10}] \label{takaovi} Oletetaan, että halutaan selvittää muuttujan X kausaalista vaikutusta muuttujaan Y. Joukko $\s$ on \emph{riittävä} vaikutuksen selvittämiseen (sufficient for adjustment), kun seuraavat ehdot ovat voimassa: \begin{enumerate}[(1)] \item Yksikään joukon $\s$ alkioista ei ole solmun X jälkeläinen. -\item Joukon $\s$ alkiot katkaisevat kaikki määritelmän \ref{d_sep} mukaiset polut solmusta X solmuun Y. +\item Joukon $\s$ alkiot katkaisevat kaikki määritelmän \ref{d_sep} mukaiset kiertoreitit solmusta X solmuun Y. Kiertoreittejä ovat polut, jotka päättyvät muuttujaan $X$ osoittavaan nuoleen. \end{enumerate} \end{maar} diff --git a/analysis_and_scripts/Analysis_07MAY2019_new.ipynb b/analysis_and_scripts/Analysis_07MAY2019_new.ipynb index ec0494b1acddd60f9da96cdd2e953277a7b2cdd6..cd2b82407a7c952a66283df283086d7a6b8c70e9 100644 --- a/analysis_and_scripts/Analysis_07MAY2019_new.ipynb +++ b/analysis_and_scripts/Analysis_07MAY2019_new.ipynb @@ -7,7 +7,7 @@ }, "source": [ "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n", - "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Causal-model\" data-toc-modified-id=\"Causal-model-1\"><span class=\"toc-item-num\">1 </span>Causal model</a></span><ul class=\"toc-item\"><li><span><a href=\"#Notes\" data-toc-modified-id=\"Notes-1.1\"><span class=\"toc-item-num\">1.1 </span>Notes</a></span></li></ul></li><li><span><a href=\"#Data-sets\" data-toc-modified-id=\"Data-sets-2\"><span class=\"toc-item-num\">2 </span>Data sets</a></span><ul class=\"toc-item\"><li><span><a href=\"#Synthetic-data-with-unobservables\" data-toc-modified-id=\"Synthetic-data-with-unobservables-2.1\"><span class=\"toc-item-num\">2.1 </span>Synthetic data with unobservables</a></span></li><li><span><a href=\"#Data-without-unobservables\" data-toc-modified-id=\"Data-without-unobservables-2.2\"><span class=\"toc-item-num\">2.2 </span>Data without unobservables</a></span></li></ul></li><li><span><a href=\"#Algorithms\" data-toc-modified-id=\"Algorithms-3\"><span class=\"toc-item-num\">3 </span>Algorithms</a></span><ul class=\"toc-item\"><li><span><a href=\"#Contraction-algorithm\" data-toc-modified-id=\"Contraction-algorithm-3.1\"><span class=\"toc-item-num\">3.1 </span>Contraction algorithm</a></span></li><li><span><a href=\"#Causal-algorithm\" data-toc-modified-id=\"Causal-algorithm-3.2\"><span class=\"toc-item-num\">3.2 </span>Causal algorithm</a></span></li></ul></li><li><span><a href=\"#Performance-comparison\" data-toc-modified-id=\"Performance-comparison-4\"><span class=\"toc-item-num\">4 </span>Performance comparison</a></span><ul class=\"toc-item\"><li><span><a href=\"#With-unobservables-in-the-data\" data-toc-modified-id=\"With-unobservables-in-the-data-4.1\"><span class=\"toc-item-num\">4.1 </span>With unobservables in the data</a></span><ul class=\"toc-item\"><li><span><a href=\"#Predictive-models\" data-toc-modified-id=\"Predictive-models-4.1.1\"><span class=\"toc-item-num\">4.1.1 </span>Predictive models</a></span></li><li><span><a href=\"#Visual-comparison\" data-toc-modified-id=\"Visual-comparison-4.1.2\"><span class=\"toc-item-num\">4.1.2 </span>Visual comparison</a></span></li></ul></li><li><span><a href=\"#Without-unobservables\" data-toc-modified-id=\"Without-unobservables-4.2\"><span class=\"toc-item-num\">4.2 </span>Without unobservables</a></span><ul class=\"toc-item\"><li><span><a href=\"#Predictive-model\" data-toc-modified-id=\"Predictive-model-4.2.1\"><span class=\"toc-item-num\">4.2.1 </span>Predictive model</a></span></li></ul></li></ul></li></ul></div>" + "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Causal-model\" data-toc-modified-id=\"Causal-model-1\"><span class=\"toc-item-num\">1 </span>Causal model</a></span><ul class=\"toc-item\"><li><span><a href=\"#Notes\" data-toc-modified-id=\"Notes-1.1\"><span class=\"toc-item-num\">1.1 </span>Notes</a></span></li></ul></li><li><span><a href=\"#Data-sets\" data-toc-modified-id=\"Data-sets-2\"><span class=\"toc-item-num\">2 </span>Data sets</a></span><ul class=\"toc-item\"><li><span><a href=\"#Synthetic-data-with-unobservables\" data-toc-modified-id=\"Synthetic-data-with-unobservables-2.1\"><span class=\"toc-item-num\">2.1 </span>Synthetic data with unobservables</a></span></li><li><span><a href=\"#Data-without-unobservables\" data-toc-modified-id=\"Data-without-unobservables-2.2\"><span class=\"toc-item-num\">2.2 </span>Data without unobservables</a></span></li></ul></li><li><span><a href=\"#Algorithms\" data-toc-modified-id=\"Algorithms-3\"><span class=\"toc-item-num\">3 </span>Algorithms</a></span><ul class=\"toc-item\"><li><span><a href=\"#Contraction-algorithm\" data-toc-modified-id=\"Contraction-algorithm-3.1\"><span class=\"toc-item-num\">3.1 </span>Contraction algorithm</a></span></li><li><span><a href=\"#Causal-approach---metrics\" data-toc-modified-id=\"Causal-approach---metrics-3.2\"><span class=\"toc-item-num\">3.2 </span>Causal approach - metrics</a></span></li></ul></li><li><span><a href=\"#Performance-comparison\" data-toc-modified-id=\"Performance-comparison-4\"><span class=\"toc-item-num\">4 </span>Performance comparison</a></span><ul class=\"toc-item\"><li><span><a href=\"#With-unobservables-in-the-data\" data-toc-modified-id=\"With-unobservables-in-the-data-4.1\"><span class=\"toc-item-num\">4.1 </span>With unobservables in the data</a></span><ul class=\"toc-item\"><li><span><a href=\"#Predictive-model\" data-toc-modified-id=\"Predictive-model-4.1.1\"><span class=\"toc-item-num\">4.1.1 </span>Predictive model</a></span></li><li><span><a href=\"#Visual-comparison\" data-toc-modified-id=\"Visual-comparison-4.1.2\"><span class=\"toc-item-num\">4.1.2 </span>Visual comparison</a></span></li></ul></li><li><span><a href=\"#Without-unobservables\" data-toc-modified-id=\"Without-unobservables-4.2\"><span class=\"toc-item-num\">4.2 </span>Without unobservables</a></span><ul class=\"toc-item\"><li><span><a href=\"#Predictive-model\" data-toc-modified-id=\"Predictive-model-4.2.1\"><span class=\"toc-item-num\">4.2.1 </span>Predictive model</a></span></li><li><span><a href=\"#Visual-comparison\" data-toc-modified-id=\"Visual-comparison-4.2.2\"><span class=\"toc-item-num\">4.2.2 </span>Visual comparison</a></span></li></ul></li></ul></li></ul></div>" ] }, { @@ -54,7 +54,7 @@ }, { "cell_type": "code", - "execution_count": 97, + "execution_count": 52, "metadata": {}, "outputs": [], "source": [ @@ -83,9 +83,11 @@ "\n", "import warnings\n", "\n", + "\n", "def fxn():\n", " warnings.warn(\"deprecated\", DeprecationWarning)\n", "\n", + "\n", "with warnings.catch_warnings():\n", " warnings.simplefilter(\"ignore\")\n", " fxn()" @@ -120,7 +122,7 @@ }, { "cell_type": "code", - "execution_count": 98, + "execution_count": 53, "metadata": {}, "outputs": [ { @@ -158,20 +160,20 @@ " <tbody>\n", " <tr>\n", " <th>0</th>\n", - " <td>16267</td>\n", - " <td>6842</td>\n", - " <td>23109</td>\n", + " <td>17263</td>\n", + " <td>7585</td>\n", + " <td>24848</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", - " <td>8765</td>\n", - " <td>18126</td>\n", - " <td>26891</td>\n", + " <td>7931</td>\n", + " <td>17221</td>\n", + " <td>25152</td>\n", " </tr>\n", " <tr>\n", " <th>All</th>\n", - " <td>25032</td>\n", - " <td>24968</td>\n", + " <td>25194</td>\n", + " <td>24806</td>\n", " <td>50000</td>\n", " </tr>\n", " </tbody>\n", @@ -181,12 +183,12 @@ "text/plain": [ "result_Y 0.0 1.0 All\n", "decision_T \n", - "0 16267 6842 23109\n", - "1 8765 18126 26891\n", - "All 25032 24968 50000" + "0 17263 7585 24848\n", + "1 7931 17221 25152\n", + "All 25194 24806 50000" ] }, - "execution_count": 98, + "execution_count": 53, "metadata": {}, "output_type": "execute_result" } @@ -195,9 +197,11 @@ "# Set seed for reproducibility\n", "#npr.seed(0)\n", "\n", + "\n", "def sigmoid(x):\n", " return 1 / (1 + np.exp(-x))\n", "\n", + "\n", "def generateData(nJudges_M=100,\n", " nSubjects_N=500,\n", " beta_X=1.0,\n", @@ -223,7 +227,7 @@ "\n", " # 0 if P(Y = 0| X = x; Z = z; W = w) >= 0.5 , 1 otherwise\n", " result_Y = 1 - probabilities_Y.round()\n", - " \n", + "\n", " # For the conditional probabilities of T we add noise ~ N(0, 0.1)\n", " probabilities_T = sigmoid(beta_X * X + beta_Z * Z)\n", " probabilities_T += npr.normal(0, np.sqrt(0.1), nJudges_M * nSubjects_N)\n", @@ -264,7 +268,7 @@ }, { "cell_type": "code", - "execution_count": 99, + "execution_count": 54, "metadata": {}, "outputs": [ { @@ -308,11 +312,11 @@ " <tbody>\n", " <tr>\n", " <th>0.0</th>\n", - " <td>4317</td>\n", + " <td>3922</td>\n", " </tr>\n", " <tr>\n", " <th>1.0</th>\n", - " <td>9047</td>\n", + " <td>8566</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", @@ -321,11 +325,11 @@ "text/plain": [ "decision_T 1\n", "result_Y \n", - "0.0 4317\n", - "1.0 9047" + "0.0 3922\n", + "1.0 8566" ] }, - "execution_count": 99, + "execution_count": 54, "metadata": {}, "output_type": "execute_result" } @@ -342,7 +346,8 @@ "test_labeled = test.copy()\n", "\n", "# Set results as NA if decision is negative.\n", - "train_labeled.result_Y = np.where(train.decision_T == 0, np.nan, train.result_Y)\n", + "train_labeled.result_Y = np.where(train.decision_T == 0, np.nan,\n", + " train.result_Y)\n", "test_labeled.result_Y = np.where(test.decision_T == 0, np.nan, test.result_Y)\n", "\n", "print(train_labeled.shape)\n", @@ -378,15 +383,14 @@ }, { "cell_type": "code", - "execution_count": 100, + "execution_count": 55, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "['judgeID_J' 'acceptanceRate_R' 'X' 'probabilities_Y' 'result_Y'\n", - " 'decision_T']\n" + "Whole data:\n" ] }, { @@ -424,20 +428,20 @@ " <tbody>\n", " <tr>\n", " <th>0</th>\n", - " <td>15791</td>\n", - " <td>8833</td>\n", - " <td>24624</td>\n", + " <td>16220</td>\n", + " <td>8743</td>\n", + " <td>24963</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", - " <td>9157</td>\n", - " <td>16219</td>\n", - " <td>25376</td>\n", + " <td>8889</td>\n", + " <td>16148</td>\n", + " <td>25037</td>\n", " </tr>\n", " <tr>\n", " <th>All</th>\n", - " <td>24948</td>\n", - " <td>25052</td>\n", + " <td>25109</td>\n", + " <td>24891</td>\n", " <td>50000</td>\n", " </tr>\n", " </tbody>\n", @@ -447,14 +451,21 @@ "text/plain": [ "result_Y 0 1 All\n", "decision_T \n", - "0 15791 8833 24624\n", - "1 9157 16219 25376\n", - "All 24948 25052 50000" + "0 16220 8743 24963\n", + "1 8889 16148 25037\n", + "All 25109 24891 50000" ] }, "metadata": {}, "output_type": "display_data" }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Training data:\n" + ] + }, { "data": { "text/html": [ @@ -490,20 +501,20 @@ " <tbody>\n", " <tr>\n", " <th>0</th>\n", - " <td>7960</td>\n", - " <td>4327</td>\n", - " <td>12287</td>\n", + " <td>8144</td>\n", + " <td>4335</td>\n", + " <td>12479</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", - " <td>4634</td>\n", - " <td>8079</td>\n", - " <td>12713</td>\n", + " <td>4375</td>\n", + " <td>8146</td>\n", + " <td>12521</td>\n", " </tr>\n", " <tr>\n", " <th>All</th>\n", - " <td>12594</td>\n", - " <td>12406</td>\n", + " <td>12519</td>\n", + " <td>12481</td>\n", " <td>25000</td>\n", " </tr>\n", " </tbody>\n", @@ -513,14 +524,21 @@ "text/plain": [ "result_Y 0 1 All\n", "decision_T \n", - "0 7960 4327 12287\n", - "1 4634 8079 12713\n", - "All 12594 12406 25000" + "0 8144 4335 12479\n", + "1 4375 8146 12521\n", + "All 12519 12481 25000" ] }, "metadata": {}, "output_type": "display_data" }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test data:\n" + ] + }, { "data": { "text/html": [ @@ -556,20 +574,20 @@ " <tbody>\n", " <tr>\n", " <th>0</th>\n", - " <td>7831</td>\n", - " <td>4506</td>\n", - " <td>12337</td>\n", + " <td>8076</td>\n", + " <td>4408</td>\n", + " <td>12484</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", - " <td>4523</td>\n", - " <td>8140</td>\n", - " <td>12663</td>\n", + " <td>4514</td>\n", + " <td>8002</td>\n", + " <td>12516</td>\n", " </tr>\n", " <tr>\n", " <th>All</th>\n", - " <td>12354</td>\n", - " <td>12646</td>\n", + " <td>12590</td>\n", + " <td>12410</td>\n", " <td>25000</td>\n", " </tr>\n", " </tbody>\n", @@ -579,9 +597,9 @@ "text/plain": [ "result_Y 0 1 All\n", "decision_T \n", - "0 7831 4506 12337\n", - "1 4523 8140 12663\n", - "All 12354 12646 25000" + "0 8076 4408 12484\n", + "1 4514 8002 12516\n", + "All 12590 12410 25000" ] }, "metadata": {}, @@ -592,6 +610,7 @@ "# Set seed for reproducibility\n", "#npr.seed(0)\n", "\n", + "\n", "def generateDataNoUnobservables(nJudges_M=100, nSubjects_N=500, beta_X=1.0):\n", "\n", " df = pd.DataFrame()\n", @@ -607,18 +626,22 @@ " # Replicate the rates so they can be attached to the corresponding judge ID.\n", " df = df.assign(acceptanceRate_R=np.repeat(acceptance_rates, nSubjects_N))\n", "\n", - " # Sample the variables from standard Gaussian distributions.\n", + " # Sample feature X from standard Gaussian distribution.\n", " df = df.assign(X=npr.normal(size=nJudges_M * nSubjects_N))\n", "\n", + " # Calculate P(Y=0|X=x) = 1 / (1 + exp(-beta_X * x)) = sigmoid(beta_X * x))\n", " df = df.assign(probabilities_Y=sigmoid(beta_X * df.X))\n", "\n", - " # Y ~ Bernoulli(sigmoid(beta_X * x))\n", + " # Draw Y ~ Bernoulli(sigmoid(beta_X * x))\n", " df = df.assign(result_Y=npr.binomial(\n", " n=1, p=df.probabilities_Y, size=nJudges_M * nSubjects_N))\n", "\n", - " # Sort by judges then probabilities in decreasing order.\n", - " # I.e. most dangerous are last.\n", - " df = df.sort_values(by=[\"judgeID_J\", \"probabilities_Y\"], ascending=True)\n", + " # Invert the probabilities. ELABORATE COMMENT!\n", + " df.probabilities_Y = 1 - df.probabilities_Y\n", + "\n", + " # Sort by judges then probabilities in increasing order.\n", + " # I.e. the most dangerous for each judge are first.\n", + " df = df.sort_values(by=[\"judgeID_J\", \"probabilities_Y\"], ascending=False)\n", "\n", " # Iterate over the data. Subject is in the top (1-r)*100% if\n", " # his within-judge-index is over acceptance threshold times\n", @@ -632,6 +655,7 @@ "\n", " return df\n", "\n", + "\n", "simple_data = generateDataNoUnobservables()\n", "\n", "# Split the data set to test and train\n", @@ -641,21 +665,22 @@ "s_test_labeled = s_test.copy()\n", "\n", "# Set results as NA if decision is negative.\n", - "s_train_labeled.result_Y = np.where(s_train.decision_T == 0, np.nan, s_train.result_Y)\n", - "s_test_labeled.result_Y = np.where(s_test.decision_T == 0, np.nan, s_test.result_Y)\n", + "s_train_labeled.result_Y = np.where(s_train.decision_T == 0, np.nan,\n", + " s_train.result_Y)\n", + "s_test_labeled.result_Y = np.where(s_test.decision_T == 0, np.nan,\n", + " s_test.result_Y)\n", "\n", - "#display(simple_data.head(20))\n", + "#display(simple_data.tail(20))\n", "\n", - "print(simple_data.columns.values)\n", + "print(\"Whole data:\")\n", + "display(\n", + " pd.crosstab(simple_data.decision_T, simple_data.result_Y, margins=True), )\n", "\n", - "display(pd.crosstab(simple_data.decision_T, simple_data.result_Y,\n", - " margins=True))\n", + "print(\"Training data:\")\n", + "display(pd.crosstab(s_train.decision_T, s_train.result_Y, margins=True))\n", "\n", - "display(pd.crosstab(s_train.decision_T, s_train.result_Y,\n", - " margins=True))\n", - "\n", - "display(pd.crosstab(s_test.decision_T, s_test.result_Y,\n", - " margins=True))" + "print(\"Test data:\")\n", + "display(pd.crosstab(s_test.decision_T, s_test.result_Y, margins=True))" ] }, { @@ -671,17 +696,12 @@ }, { "cell_type": "code", - "execution_count": 101, + "execution_count": 56, "metadata": {}, "outputs": [], "source": [ - "def contraction(df,\n", - " judgeIDJ_col,\n", - " decisionT_col,\n", - " resultY_col,\n", - " modelProbS_col,\n", - " accRateR_col,\n", - " r):\n", + "def contraction(df, judgeIDJ_col, decisionT_col, resultY_col, modelProbS_col,\n", + " accRateR_col, r):\n", " '''\n", " This is an implementation of the algorithm presented by Lakkaraju\n", " et al. in their paper \"The Selective Labels Problem: Evaluating \n", @@ -704,14 +724,17 @@ " u = The estimated failure rate at acceptance rate r.\n", " '''\n", " # Get ID of the most lenient judge.\n", - " most_lenient_ID = df[judgeIDJ_col].loc[df[accRateR_col].idxmax()]\n", + " most_lenient_ID_q = df[judgeIDJ_col].loc[df[accRateR_col].idxmax()]\n", "\n", - " # Subset\n", - " D_q = df[df[judgeIDJ_col] == most_lenient_ID].copy()\n", + " # Subset. \"D_q is the set of all observations judged by q.\"\n", + " D_q = df[df[judgeIDJ_col] == most_lenient_ID_q].copy()\n", "\n", - " # All observations of R_q have observed outcome labels\n", - " R_q = D_q[D_q[decisionT_col] == 1]\n", + " # All observations of R_q have observed outcome labels.\n", + " # \"R_q is the set of observations in D_q with observed outcome labels.\"\n", + " R_q = D_q[D_q[decisionT_col] == 1].copy()\n", "\n", + " # Sort observations in R_q in descending order of confidence scores S and\n", + " # assign to R_sort_q.\n", " # \"Observations deemed as high risk by B are at the top of this list\"\n", " R_sort_q = R_q.sort_values(by=modelProbS_col, ascending=False)\n", "\n", @@ -728,7 +751,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Causal algorithm\n", + "### Causal approach - metrics\n", "\n", "Generalized performance:\n", "\n", @@ -745,21 +768,31 @@ "where\n", "\n", "$$\n", - "F(x_0) = \\int P(x)~\\delta(P(Y=0|T=1, X=x) > P(Y=0|T=1, X=x_0)) ~ dx\n", + "f(x) = P(Y=0|T=1, X=x)\n", "$$\n", "\n", "and\n", "\n", "$$\n", - "f(x) = P(Y=0|T=1, X=x).\n", - "$$" + "F(x_0) = \\int P(x)~\\delta(P(Y=0|T=1, X=x) > P(Y=0|T=1, X=x_0)) ~ dx = \\int P(x)~\\delta(f(x) > f(x_0)) ~ dx.\n", + "$$\n" ] }, { "cell_type": "code", - "execution_count": 102, + "execution_count": 57, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "4.67 ms ± 65.1 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "20.4 ms ± 329 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", + "187 ms ± 5.24 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + ] + } + ], "source": [ "def getProbabilityForClass(x, model, class_value):\n", " '''\n", @@ -784,34 +817,40 @@ " # Get correct column of predicted class, remove extra dimensions and return.\n", " return f_values[:, model.classes_ == class_value].flatten()\n", "\n", + "\n", "def cdf(x_0, model, class_value):\n", " '''\n", " Cumulative distribution function as described above.\n", " \n", " '''\n", - " prediction = lambda x: getProbabilityForClass(np.array([x]).reshape(-1,1), model, class_value)\n", - " \n", + " prediction = lambda x: getProbabilityForClass(\n", + " np.array([x]).reshape(-1, 1), model, class_value)\n", + "\n", " prediction_x_0 = prediction(x_0)\n", - " \n", + "\n", + " x_values = np.linspace(-10, 10, 40000)\n", + "\n", + " x_preds = prediction(x_values)\n", + "\n", + " y_values = scs.norm.pdf(x_values)\n", + "\n", " results = np.zeros(x_0.shape[0])\n", - " \n", - " x_values = np.linspace(-10, 10, 50000)\n", - " \n", + "\n", " for i in range(x_0.shape[0]):\n", - " results[i] = si.simps(scs.norm.pdf(x_values) * (prediction(x_values) > prediction_x_0[i]), x=x_values)\n", - " \n", + " \n", + " y_copy = y_values.copy()\n", + " \n", + " y_copy[prediction(x_values) < prediction_x_0[i]] = 0\n", + " \n", + " results[i] = si.simps(y_copy, x=x_values)\n", + "\n", " return results\n", "\n", - "#%timeit cdf(np.ones(1), logreg, 0)\n", - "#%timeit cdf(np.ones(10), logreg, 0)\n", - "#%timeit cdf(np.ones(100), logreg, 0)\n", - "#\n", - "#x_values = np.linspace(-10, 10, 1000)\n", - "#\n", - "#print(getProbabilityForClass(s_train.X.head(1), logreg, 0))\n", - "#\n", - "#plt.plot(x_values, getProbabilityForClass(x_values, logreg, 0))\n", - "#plt.show()" + "\n", + "%timeit cdf(np.ones(1), logreg, 0)\n", + "%timeit cdf(np.ones(10), logreg, 0)\n", + "%timeit cdf(np.ones(100), logreg, 0)\n", + "#%timeit cdf(np.ones(1000), logreg, 0)" ] }, { @@ -824,14 +863,14 @@ "\n", "### With unobservables in the data\n", "\n", - "#### Predictive models\n", + "#### Predictive model\n", "\n", "Lakkaraju says that they used logistic regression. We train the predictive models using only *observed observations*, i.e. observations for which labels are available. We then predict the probability of negative outcome for all observations in the test data and attach it to our data set." ] }, { "cell_type": "code", - "execution_count": 103, + "execution_count": 74, "metadata": {}, "outputs": [], "source": [ @@ -840,8 +879,8 @@ "\n", "# fit, reshape X to be of shape (n_samples, n_features)\n", "logreg = logreg.fit(\n", - " train_labeled.X[train_labeled.decision_T == 1].values.reshape(-1, 1),\n", - " train_labeled.result_Y[train_labeled.decision_T == 1])\n", + " train_labeled.dropna().X.values.reshape(-1, 1),\n", + " train_labeled.result_Y.dropna())\n", "\n", "# predict probabilities and attach to data\n", "label_probs_logreg = logreg.predict_proba(test.X.values.reshape(-1, 1))\n", @@ -859,7 +898,7 @@ }, { "cell_type": "code", - "execution_count": 104, + "execution_count": 59, "metadata": {}, "outputs": [], "source": [ @@ -882,14 +921,14 @@ }, { "cell_type": "code", - "execution_count": 105, + "execution_count": 82, "metadata": { "scrolled": false }, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "<Figure size 1008x576 with 1 Axes>" ] @@ -904,26 +943,30 @@ "failure_rates = np.zeros((8, 5))\n", "\n", "for r in np.arange(1, 9):\n", - " \n", + "\n", " #### True evaluation\n", - " # Sort by failure probabilities, subjects with the smallest risk are first. \n", + " # Sort by failure probabilities, subjects with the smallest risk are first.\n", " test.sort_values(by='B_prob_0_logreg', inplace=True, ascending=True)\n", "\n", " to_release = int(round(test.shape[0] * r / 10))\n", "\n", - " # Calculate failure rate as the ratio of failures to successes among those \n", + " # Calculate failure rate as the ratio of failures to successes among those\n", " # who were given a positive decision, i.e. those whose probability of negative\n", " # outcome was low enough.\n", - " failure_rates[r - 1, 0] = np.mean(test.result_Y[0:to_release] == 0)\n", - " \n", + " failure_rates[r - 1, 0] = np.sum(\n", + " test.result_Y[0:to_release] == 0) / test.shape[0]\n", + "\n", " #### Labeled outcomes only\n", - " # Sort by failure probabilities, subjects with the smallest risk are first. \n", - " test_labeled.sort_values(by='B_prob_0_logreg', inplace=True, ascending=True)\n", - " \n", + " # Sort by failure probabilities, subjects with the smallest risk are first.\n", + " test_labeled.sort_values(by='B_prob_0_logreg',\n", + " inplace=True,\n", + " ascending=True)\n", + "\n", " to_release = int(round(test_labeled.shape[0] * r / 10))\n", "\n", - " failure_rates[r - 1, 1] = np.mean(test_labeled.result_Y[0:to_release] == 0)\n", - " \n", + " failure_rates[r - 1, 1] = np.sum(\n", + " test_labeled.result_Y[0:to_release] == 0) / test_labeled.shape[0]\n", + "\n", " #### Human error rate\n", " # Get judges with correct leniency as list\n", " correct_leniency_list = test_labeled.judgeID_J[\n", @@ -936,27 +979,43 @@ " # Get their failure rate, aka ratio of reoffenders to number of people judged in total\n", " failure_rates[r - 1, 2] = np.sum(\n", " released.result_Y == 0) / correct_leniency_list.shape[0]\n", - " \n", + "\n", " #### Contraction, logistic regression\n", - " failure_rates[r - 1, 3] = contraction(\n", - " test_labeled, 'judgeID_J', 'decision_T', 'result_Y', 'B_prob_0_logreg',\n", - " 'acceptanceRate_R', r / 10)\n", + " failure_rates[r - 1, 3] = contraction(test_labeled, 'judgeID_J',\n", + " 'decision_T', 'result_Y',\n", + " 'B_prob_0_logreg',\n", + " 'acceptanceRate_R', r / 10)\n", "\n", - " #### Causal effect - \"vanilla\" (wrong) model\n", + " #### Causal effect\n", " # Integral of P(Y=0 | T=1, X=x)*P(T=1 | R=r, X=x)*P(X=x) from negative to\n", " # positive infinity.\n", - " failure_rates[r - 1, 4] = si.quad(lambda x: getProbabilityForClass(np.array([x]), logreg, 0) * \n", - " getProbabilityForClass(np.array([[x, r/10]]), decision_model, 1) * \n", - " scs.norm.pdf(x), -np.inf, np.inf)[0]\n", + " failure_rates[r - 1, 4] = np.sum((test_labeled.dropna().result_Y == 0) & (\n", + " cdf(test_labeled.dropna().X, logreg, 0) < r /\n", + " 10)) / test_labeled.dropna().result_Y.shape[0]\n", "\n", "# Error bars TBA\n", "\n", "plt.figure(figsize=(14, 8))\n", - "plt.plot(np.arange(0.1, 0.9, .1), failure_rates[:, 0], label='True Evaluation', c='green')\n", - "plt.plot(np.arange(0.1, 0.9, .1), failure_rates[:, 1], label='Labeled outcomes', c='black')\n", - "plt.plot(np.arange(0.1, 0.9, .1), failure_rates[:, 2], label='Human evaluation', c='red')\n", - "plt.plot(np.arange(0.1, 0.9, .1), failure_rates[:, 3], label='Contraction, log.', c='blue')\n", - "plt.plot(np.arange(0.1, 0.9, .1), failure_rates[:, 4], label='Causal effect', c='magenta')\n", + "plt.plot(np.arange(0.1, 0.9, .1),\n", + " failure_rates[:, 0],\n", + " label='True Evaluation',\n", + " c='green')\n", + "plt.plot(np.arange(0.1, 0.9, .1),\n", + " failure_rates[:, 1],\n", + " label='Labeled outcomes',\n", + " c='black')\n", + "plt.plot(np.arange(0.1, 0.9, .1),\n", + " failure_rates[:, 2],\n", + " label='Human evaluation',\n", + " c='red')\n", + "plt.plot(np.arange(0.1, 0.9, .1),\n", + " failure_rates[:, 3],\n", + " label='Contraction, log.',\n", + " c='blue')\n", + "plt.plot(np.arange(0.1, 0.9, .1),\n", + " failure_rates[:, 4],\n", + " label='Causal effect',\n", + " c='magenta')\n", "\n", "plt.title('Failure rate vs. Acceptance rate')\n", "plt.xlabel('Acceptance rate')\n", @@ -967,65 +1026,60 @@ ] }, { - "cell_type": "code", - "execution_count": 106, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "# Below are estimates for P(Y=0 | do(R=0)) and P(Y=0 | do(R=1))\n", - "#r = 0.0\n", - "#print(r, si.quad(lambda x: f(np.array([[x, r]]), decision_model, 1) * \\\n", - "# f(np.array([x]), logreg, 0) * scs.norm.pdf(x), -np.inf, np.inf))\n", - "#\n", - "#r = 1.0\n", - "#print(r, si.quad(lambda x: f(np.array([[x, r]]), decision_model, 1) * \\\n", - "# f(np.array([x]), logreg, 0) * scs.norm.pdf(x), -np.inf, np.inf))" + "### Without unobservables\n", + "\n", + "\n", + "#### Predictive model\n", + "\n", + "First build predictive models to give to cdf function." ] }, { - "cell_type": "markdown", - "metadata": {}, + "cell_type": "code", + "execution_count": 83, + "metadata": { + "scrolled": false + }, + "outputs": [], "source": [ - "So it can be concluded that:\n", + "s_logreg = LogisticRegression(solver=\"lbfgs\")\n", + "\n", + "s_logreg = s_logreg.fit(s_train_labeled.dropna().X.values.reshape(-1, 1),\n", + " s_train_labeled.result_Y.dropna())\n", "\n", - "\\begin{equation*}\n", - "P(Y=0 | \\text{do}(R=0)) \\approx 0.018 \\\\\n", - "P(Y=0 | \\text{do}(R=1)) \\approx 0.340 \\\\\n", - "\\end{equation*}" + "s_test = s_test.assign(\n", + " pred_Y=s_logreg.predict_proba(s_test.X.values.reshape(-1, 1))[:, 0])\n", + "s_test_labeled = s_test_labeled.assign(\n", + " pred_Y=s_logreg.predict_proba(s_test_labeled.X.values.reshape(-1, 1))[:, 0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Without unobservables\n", - "\n", - "\n", - "#### Predictive model\n" + "#### Visual comparison" ] }, { "cell_type": "code", - "execution_count": 107, - "metadata": {}, + "execution_count": 81, + "metadata": { + "scrolled": false + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "1\n", - "2\n", - "3\n", - "4\n", - "5\n", - "6\n", - "7\n", - "8\n" + "1 2 3 4 5 6 7 8 " ] }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "<Figure size 1008x504 with 1 Axes>" ] @@ -1037,94 +1091,64 @@ } ], "source": [ + "f_rates_true = np.zeros(0)\n", + "f_rates_human = np.zeros(0)\n", "f_rates_cont = np.zeros(0)\n", - "#f_rates_caus = np.zeros(0)\n", + "f_rates_caus = np.zeros(0)\n", "x_vals = np.arange(1, 9) / 10\n", "\n", "for r in range(1, 9):\n", - " f_rates_cont = np.append(f_rates_cont,\n", - " contraction(s_train_labeled, 'judgeID_J', 'decision_T', 'result_Y',\n", - " 'probabilities_Y', 'acceptanceRate_R', r / 10))\n", - " print(r)\n", - " #f_rates_caus = np.append(f_rates_caus, \n", - " # np.mean((s_train.result_Y[s_train.decision_T==1] == 0) & (cdf(s_train.X[s_train.decision_T==1], logreg, 0) < r/10)))\n", " \n", - "plt.plot(x_vals, f_rates_cont, label=\"Contraction\")\n", - "plt.plot(x_vals, f_rates_caus, label=\"Causal\")\n", - "plt.title('Failure rate vs. Acceptance rate, simple data')\n", - "plt.xlabel('Acceptance rate')\n", - "plt.ylabel('Failure rate')\n", - "plt.legend()\n", - "plt.grid()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 122, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 1008x504 with 1 Axes>" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "f_rates_true = np.zeros(0)\n", - "f_rates_labeled = np.zeros(0)\n", - "f_rates_human = np.zeros(0)\n", - "\n", - "for r in range(1, 9):\n", + " f_rates_cont = np.append(\n", + " f_rates_cont,\n", + " contraction(s_test_labeled, 'judgeID_J', 'decision_T', 'result_Y',\n", + " 'pred_Y', 'acceptanceRate_R', r / 10))\n", + " print(r, end=\" \")\n", + " f_rates_caus = np.append(\n", + " f_rates_caus,\n", + " np.sum((s_test_labeled.dropna().result_Y== 0) &\n", + " (cdf(s_test_labeled.dropna().X, s_logreg, 0) < r / 10)) /\n", + " s_test_labeled.dropna().result_Y.shape[0])\n", + " \n", " #### True evaluation\n", - " # Sort by failure probabilities, subjects with the smallest risk are first. \n", - " s_sorted = s_test.sort_values(by='probabilities_Y', inplace=False, ascending=False)\n", + " # Sort by failure probabilities, subjects with the smallest risk are first.\n", + " s_sorted = s_test.sort_values(by='probabilities_Y',\n", + " inplace=False,\n", + " ascending=True)\n", "\n", " to_release = int(round(s_sorted.shape[0] * r / 10))\n", "\n", - " # Calculate failure rate as the ratio of failures to successes among those \n", + " # Calculate failure rate as the ratio of failures to successes among those\n", " # who were given a positive decision, i.e. those whose probability of negative\n", " # outcome was low enough.\n", - " f_rates_true = np.append(f_rates_true, np.mean(s_sorted.result_Y[0:to_release] == 0))\n", - " \n", - " #### Labeled outcomes only\n", - " # Sort by failure probabilities, subjects with the smallest risk are first. \n", - " s_test_labeled.sort_values(by='probabilities_Y', inplace=True, ascending=False)\n", - " \n", - " to_release = int(round(s_test_labeled[s_test_labelead.decision_T==1].shape[0] * r / 10))\n", + " f_rates_true = np.append(f_rates_true,\n", + " np.sum(s_sorted.result_Y[0:to_release] == 0)/s_sorted.shape[0])\n", "\n", - " f_rates_labeled = np.append(f_rates_labeled, np.mean(s_test_labeled.result_Y[0:to_release] == 0))\n", - " \n", " #### Human error rate\n", " # Get judges with correct leniency as list\n", " correct_leniency_list = s_test_labeled.judgeID_J[\n", " s_test_labeled['acceptanceRate_R'].round(1) == r / 10].values\n", "\n", " # Released are the people they judged and released, T = 1\n", - " released = s_test_labeled[s_test_labeled.judgeID_J.isin(correct_leniency_list)\n", - " & (s_test_labeled.decision_T == 1)]\n", - "\n", - " # Get their failure rate, aka ratio of reoffenders to number of people judged in total\n", - " f_rates_human = np.append(f_rates_human, np.sum(\n", - " released.result_Y == 0) / correct_leniency_list.shape[0])\n", + " released = s_test_labeled[\n", + " s_test_labeled.judgeID_J.isin(correct_leniency_list)\n", + " & (s_test_labeled.decision_T == 1)]\n", " \n", + " # Get their failure rate, aka ratio of reoffenders to number of people judged in total\n", + " f_rates_human = np.append(\n", + " f_rates_human,\n", + " np.sum(released.result_Y == 0) / correct_leniency_list.shape[0])\n", + "\n", "plt.plot(x_vals, f_rates_cont, label=\"Contraction\")\n", "plt.plot(x_vals, f_rates_caus, label=\"Causal\")\n", "plt.plot(x_vals, f_rates_true, label=\"True evaluation\")\n", - "plt.plot(x_vals, f_rates_labeled, label=\"Labeled outcomes\")\n", "plt.plot(x_vals, f_rates_human, label=\"Human evaluation\")\n", "plt.title('Failure rate vs. Acceptance rate, simple data')\n", "plt.xlabel('Acceptance rate')\n", "plt.ylabel('Failure rate')\n", "plt.legend()\n", "plt.grid()\n", + "#plt.yscale(value=\"log\")\n", "plt.show()" ] }