Newer
Older
" if x.ndim == 1:\n",
" # if x is vector, transform to column matrix.\n",
" f_values = model.predict_proba(np.array(x).reshape(-1, 1))\n",
" else:\n",
" f_values = model.predict_proba(x)\n",
"\n",
" return f_values[:, model.classes_ == failure_value].flatten()\n",
"def ep(r, df, result_col, feature_cols, model, failure_value):\n",
" '''\n",
" Returns:\n",
" Empirical performance, i.e. percentage of recidivists. \n",
" \n",
" Parameters:\n",
" df = test data, pandas DataFrame\n",
" result_col = String (list), name of column containing the binarized results.\n",
" feature_cols = String (list), name of columns containge individual features.\n",
" model = trained sklearn classifier \n",
" failure_value = value obtained from the model.classes_ representing the \n",
" unwanted event label (usually 0 or 1).\n",
" '''\n",
" rates = np.zeros_like(r)\n",
" for i in range(len(rates)):\n",
" rates[i] = np.mean((df[result_col] == failure_value) &\n",
" (f(df[feature_cols], model, failure_value) < r[i]))\n",
"def gp(r, df, feature_cols, y_model, x_model, failure_value):\n",
" '''\n",
" Returns:\n",
" Generalized performance\n",
" \n",
" Parameters:\n",
" r = leniency rate\n",
" df = test data, pandas DataFrame\n",
" feature_cols = String (list), name of columns containing individual features.\n",
" y_model = trained sklearn classifier to predict response\n",
" x_model = model of P(X=x)\n",
" failure_value = value obtained from the model.classes_ representing the \n",
" unwanted event label.\n",
" preds = f(df[feature_cols], y_model, failure_value)\n",
" \n",
" return np.sum(preds * (preds < r) * x_model(df[feature_cols]))"
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Performance comparison\n",
"\n",
"Below we try to replicate the results obtained by Lakkaraju and compare their model's performance to the one of ours.\n",
"Lakkaraju says that they used logistic regression to predict recidivism. We models using only *observed observations*, i.e. defendants that were granted bail and are in the train set. We then predict the probability of recidivism for all observations in the test data and attach it to our data set. I also applied random forest classifier."
"metadata": {},
"outputs": [],
"source": [
"# instantiate the model (using the default parameters)\n",
"logreg = LogisticRegression(solver='lbfgs')\n",
"\n",
"# fit, reshape X to be of shape (n_samples, n_features)\n",
"logreg.fit(train_labeled.X.values.reshape(-1, 1), train_labeled.result_Y)\n",
"\n",
"# predict probabilities and attach to data\n",
"label_probs_logreg = logreg.predict_proba(test.X.values.reshape(-1, 1))\n",
"test = test.assign(B_prob_0_logreg=label_probs_logreg[:, 0])\n",
"label_probs_logreg = logreg.predict_proba(test_labeled.X.values.reshape(-1, 1))\n",
"test_labeled = test_labeled.assign(B_prob_0_logreg=label_probs_logreg[:, 0])\n",
"test_labeled = test_labeled.assign(B_prob_1_logreg=label_probs_logreg[:, 1])\n",
"\n",
"# instantiate the model (using the default parameters)\n",
"forest = RandomForestClassifier(n_estimators=400, max_depth=8, random_state=0)\n",
"# fit, reshape X to be of shape (n_samples, n_features)\n",
"forest = forest.fit(train_labeled.X.values.reshape(-1, 1), train_labeled.result_Y)\n",
"\n",
"# predict probabilities and attach to data\n",
"label_probs_forest = forest.predict_proba(test.X.values.reshape(-1, 1))\n",
"test = test.assign(B_prob_0_forest=label_probs_forest[:, 0])\n",
"\n",
"label_probs_forest = forest.predict_proba(test_labeled.X.values.reshape(-1, 1))\n",
"test_labeled = test_labeled.assign(B_prob_0_forest=label_probs_forest[:, 0])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's plot the failure rates against the acceptance rates using the difference."
]
},
{
"cell_type": "code",
"metadata": {
"scrolled": false
},
"image/png": 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\n",
"text/plain": [
"<Figure size 1008x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[0. 0.0047 0. 0.0083 0.0169 0.0204]\n",
" [0.0142 0.019 0.0026 0.0208 0.0546 0.0522]\n",
" [0.0332 0.0332 0.0077 0.0417 0.0909 0.0904]\n",
" [0.0616 0.0616 0.05 0.0708 0.1255 0.1227]\n",
" [0.0948 0.09 0.1245 0.1167 0.1576 0.1566]\n",
" [0.1469 0.1517 0.2043 0.1625 0.1819 0.1899]\n",
" [0.1943 0.1991 0.2818 0.2167 0.1997 0.2039]\n",
" [0.2512 0.2512 0.3913 0.3125 0.2139 0.2183]]\n"
"failure_rates = np.zeros((8, 6))\n",
"# sort whole test data by \n",
"#test_sorted = test.sort_values(by='B_prob_0_logreg', ascending=False)\n",
"\n",
" ## Contraction, logistic regression\n",
" failure_rates[r - 1, 0] = contraction(\n",
" test_labeled, 'judgeID_J', 'decision_T', 'result_Y',\n",
" 'B_prob_0_logreg', 'acceptanceRate_R', r / 10, False)\n",
" \n",
" ## Contraction, random forest\n",
" failure_rates[r - 1, 1] = contraction(\n",
" test_labeled, 'judgeID_J', 'decision_T', 'result_Y',\n",
" 'B_prob_0_forest', 'acceptanceRate_R', r / 10, False)\n",
" ## Human error rate - Correct?\n",
" # Get judges with correct leniency as list\n",
" correct_leniency_list = test_labeled.judgeID_J[test_labeled['acceptanceRate_R'].round(1) ==\n",
" r / 10]\n",
"\n",
" # Released are the people they judged and released, T = 1\n",
" released = test_labeled[test_labeled.judgeID_J.isin(correct_leniency_list)]\n",
"\n",
" # 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",
" ## True evaluation -- didn't mention using contraction here???\n",
" failure_rates[r - 1, 3] = contraction(test, 'judgeID_J', 'decision_T',\n",
" 'result_Y', 'B_prob_0_logreg',\n",
" 'acceptanceRate_R', r / 10, False)\n",
"\n",
" ## Causal model with logistic regression\n",
" failure_rates[r - 1, 4] = ep([r / 10], test_labeled, 'result_Y', 'X', logreg, 0)\n",
" ## Causal model with random forest classifier\n",
" failure_rates[r - 1, 5] = ep([r / 10], test_labeled, 'result_Y', 'X', forest, 0)\n",
"\n",
"# klassifikaatioille scipy.stats semin kautta error barit xerr ja yerr argumenttien kautta\n",
"\n",
"plt.figure(figsize=(14, 8))\n",
"plt.plot(np.arange(0.1, 0.9, .1), failure_rates[:, 0], label='Contraction, logistic')\n",
"#plt.plot(np.arange(0.1, 0.9, .1), failure_rates[:, 1], label='Contraction, forest')\n",
"plt.plot(np.arange(0.1, 0.9, .1), failure_rates[:, 2], label='\"Human judges\"')\n",
"plt.plot(np.arange(0.1, 0.9, .1), failure_rates[:, 3], label='True Evaluation')\n",
"\n",
"plt.plot(np.arange(0.1, 0.9, .1), failure_rates[:, 4], label='Causal model, log.')\n",
"plt.plot(np.arange(0.1, 0.9, .1), failure_rates[:, 5], label='Causal model, r.f.')\n",
"plt.title('Failure rate vs. Acceptance rate')\n",
"plt.xlabel('Acceptance rate')\n",
"plt.ylabel('Failure rate')\n",
"plt.legend()\n",
"plt.show()\n",
"\n",
"with np.printoptions(precision=4, suppress=True):\n",
" print(failure_rates)"
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Thoughts:**\n",
"\n",
"Failure rates still too high for about 10 percentage points compared to Lakkaraju paper. Failure rates will change if seed is changed (e.g. with seed 0 contraction's failure rates are approximately 0.31, causal doesn't change that much). It seems like the contraction or our model is some how predicting the wrong thing. Behavior after 0.5 is not consistent? (Curves curve down in Lakkaraju's paper. + Human evaluation curve jumps to the wrong side.) Have to check some rounding rules."
]
},
{
"cell_type": "code",
"metadata": {
"scrolled": false
},
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\n",
"text/plain": [
"<Figure size 1008x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"x_vals = np.linspace(0, 1, 100)\n",
"y_vals = ep(x_vals, test_labeled, 'result_Y', 'X', logreg, 0)\n",
"y_vals2 = ep(x_vals, test_labeled, 'result_Y', 'X', logreg, 1)\n",
"\n",
"y_vals3 = ep(x_vals, test, 'result_Y', 'X', logreg, 0)\n",
"y_vals4 = ep(x_vals, test, 'result_Y', 'X', logreg, 1)\n",
"\n",
"plt.figure(figsize=(14, 8))\n",
"plt.plot(x_vals, y_vals)\n",
"plt.plot(x_vals, y_vals2)\n",
"plt.plot(x_vals, y_vals3)\n",
"plt.plot(x_vals, y_vals4)\n",
"plt.show()"
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### On COMPAS data\n",
"\n",
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"#### Predictive models\n",
"\n",
"Let's build the predictive models (first here random forest and logistic regression). Some of our variables are string so they will first have to be transformed to be dummy / indicator variables."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"# convert string values to dummies, drop first so full rank\n",
"compas_dummy = pd.get_dummies(compas, columns=['c_charge_degree', 'race', 'age_cat', 'score_text', 'sex'], drop_first=True)\n",
"\n",
"########\n",
"\n",
"predict_columns = ['priors_count', 'days_b_screening_arrest', 'length_of_stay',\n",
" 'c_charge_degree_M', 'race_Asian', 'race_Caucasian', 'race_Hispanic',\n",
" 'race_Native American', 'race_Other', 'age_cat_Greater than 45',\n",
" 'age_cat_Less than 25', 'score_text_Low', 'score_text_Medium', 'sex_Male']\n",
"\n",
"response_column = 'two_year_recid'\n",
"\n",
"# instantiate the model (using the default parameters)\n",
"logreg_c = LogisticRegression(solver='lbfgs', max_iter=1000)\n",
"\n",
"# fit, reshape X to be of shape (n_samples, n_features)\n",
"logreg_c.fit(compas_dummy[predict_columns], compas_dummy[response_column])\n",
"\n",
"# predict probabilities and attach to data\n",
"#label_probs_logreg = logreg_c.predict_proba(test.X.values.reshape(-1, 1))\n",
"#test = test.assign(B_prob_0_machine=label_probs_logreg[:, 0])\n",
"\n",
"########\n",
"\n",
"# instantiate the model\n",
"forest_c = RandomForestClassifier(n_estimators=300, max_depth=5, random_state=0)\n",
"\n",
"# fit, reshape X to be of shape (n_samples, n_features)\n",
"forest_c = forest.fit(compas_dummy[predict_columns], compas_dummy[response_column])\n",
"\n",
"# predict probabilities and attach to data\n",
"#label_probs_forest = forest.predict_proba(test.X.values.reshape(-1, 1))\n",
"#test = test.assign(B_prob_0_forest=label_probs_forest[:, 0])"
]
},
{
"cell_type": "code",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 1008x576 with 1 Axes>"
]
},
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}
],
"source": [
"failures_compas = np.zeros((11, 2))\n",
"\n",
"for r in np.arange(0, 11):\n",
" ## Causal model with logistic regression\n",
" failures_compas[r, 0] = ep([r / 10], compas_dummy, response_column, predict_columns, logreg_c, 1)\n",
" \n",
" ## Causal model with random forest classifier\n",
" failures_compas[r, 1] = ep([r / 10], compas_dummy, response_column, predict_columns, forest_c, 1)\n",
"\n",
"# klassifikaatioille scipy.stats semin kautta error barit xerr ja yerr argumenttien kautta\n",
"\n",
"plt.figure(figsize=(14, 8))\n",
"plt.plot(np.arange(0, 11) / 10, failures_compas[:, 0], label='Causal model, log.')\n",
"plt.plot(np.arange(0, 11) / 10, failures_compas[:, 1], label='Causal model, for.')\n",
"\n",
"plt.title('Failure rate vs. Acceptance rate - COMPAS')\n",
"plt.xlabel('Leniency')\n",
"plt.ylabel('Empirical performance')\n",
"plt.legend()\n",
"plt.show()\n"
},
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"source": [
"Of course if leniency is one, then the empirical performance should always converge to the proportion of false positives in the data."
]
}
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