Skip to content
Snippets Groups Projects
Analysis_07MAY2019_new.ipynb 200 KiB
Newer Older
  • Learn to ignore specific revisions
  • Riku-Laine's avatar
    Riku-Laine committed
        "         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",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "\n",
        "plt.title('Failure rate vs. Acceptance rate')\n",
        "plt.xlabel('Acceptance rate')\n",
        "plt.ylabel('Failure rate')\n",
        "plt.legend()\n",
        "plt.grid()\n",
        "plt.show()"
       ]
      },
      {
    
    Riku-Laine's avatar
    Riku-Laine committed
       "cell_type": "markdown",
    
    Riku-Laine's avatar
    Riku-Laine committed
       "metadata": {},
       "source": [
    
    Riku-Laine's avatar
    Riku-Laine committed
        "### Without unobservables\n",
        "\n",
        "\n",
        "#### Predictive model\n",
        "\n",
        "First build predictive models to give to cdf function."
    
    Riku-Laine's avatar
    Riku-Laine committed
       ]
      },
      {
    
    Riku-Laine's avatar
    Riku-Laine committed
       "cell_type": "code",
       "execution_count": 83,
       "metadata": {
        "scrolled": false
       },
       "outputs": [],
    
    Riku-Laine's avatar
    Riku-Laine committed
       "source": [
    
    Riku-Laine's avatar
    Riku-Laine committed
        "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",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "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])"
    
    Riku-Laine's avatar
    Riku-Laine committed
       ]
    
    Riku-Laine's avatar
    Riku-Laine committed
      },
      {
       "cell_type": "markdown",
       "metadata": {},
       "source": [
    
    Riku-Laine's avatar
    Riku-Laine committed
        "#### Visual comparison"
    
    Riku-Laine's avatar
    Riku-Laine committed
       ]
      },
      {
       "cell_type": "code",
    
    Riku-Laine's avatar
    Riku-Laine committed
       "execution_count": 81,
       "metadata": {
        "scrolled": false
       },
    
    Riku-Laine's avatar
    Riku-Laine committed
       "outputs": [
        {
         "name": "stdout",
         "output_type": "stream",
         "text": [
    
    Riku-Laine's avatar
    Riku-Laine committed
          "1 2 3 4 5 6 7 8 "
    
    Riku-Laine's avatar
    Riku-Laine committed
         ]
        },
        {
         "data": {
    
    Riku-Laine's avatar
    Riku-Laine committed
          "image/png": "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\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
          "text/plain": [
           "<Figure size 1008x504 with 1 Axes>"
          ]
         },
         "metadata": {
          "needs_background": "light"
         },
         "output_type": "display_data"
        }
       ],
       "source": [
    
    Riku-Laine's avatar
    Riku-Laine committed
        "f_rates_true = np.zeros(0)\n",
        "f_rates_human = np.zeros(0)\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "f_rates_cont = np.zeros(0)\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "f_rates_caus = np.zeros(0)\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "x_vals = np.arange(1, 9) / 10\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "\n",
        "for r in range(1, 9):\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "    \n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "    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",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "    #### True evaluation\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "    # 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",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "\n",
        "    to_release = int(round(s_sorted.shape[0] * r / 10))\n",
        "\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "    # Calculate failure rate as the ratio of failures to successes among those\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "    # who were given a positive decision, i.e. those whose probability of negative\n",
        "    # outcome was low enough.\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "    f_rates_true = np.append(f_rates_true,\n",
        "                             np.sum(s_sorted.result_Y[0:to_release] == 0)/s_sorted.shape[0])\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "\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",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "    released = s_test_labeled[\n",
        "        s_test_labeled.judgeID_J.isin(correct_leniency_list)\n",
        "        & (s_test_labeled.decision_T == 1)]\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "    \n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "    # 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",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "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_human, label=\"Human evaluation\")\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "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",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "#plt.yscale(value=\"log\")\n",
    
    Riku-Laine's avatar
    Riku-Laine committed
        "plt.show()"
       ]
    
    Riku-Laine's avatar
    Riku-Laine committed
      }
     ],
     "metadata": {
      "kernelspec": {
       "display_name": "Python 3",
       "language": "python",
       "name": "python3"
      },
      "language_info": {
       "codemirror_mode": {
        "name": "ipython",
        "version": 3
       },
       "file_extension": ".py",
       "mimetype": "text/x-python",
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
    
    Riku-Laine's avatar
    Riku-Laine committed
       "version": "3.7.3"
    
    Riku-Laine's avatar
    Riku-Laine committed
      },
      "toc": {
       "base_numbering": 1,
       "nav_menu": {},
       "number_sections": true,
       "sideBar": true,
       "skip_h1_title": true,
       "title_cell": "Table of Contents",
       "title_sidebar": "Contents",
       "toc_cell": true,
    
    Riku-Laine's avatar
    Riku-Laine committed
       "toc_position": {
        "height": "calc(100% - 180px)",
        "left": "10px",
        "top": "150px",
        "width": "300.7px"
       },
    
    Riku-Laine's avatar
    Riku-Laine committed
       "toc_section_display": true,
    
    Riku-Laine's avatar
    Riku-Laine committed
       "toc_window_display": true
    
    Riku-Laine's avatar
    Riku-Laine committed
      },
      "varInspector": {
       "cols": {
        "lenName": 16,
        "lenType": 16,
        "lenVar": 40
       },
       "kernels_config": {
        "python": {
         "delete_cmd_postfix": "",
         "delete_cmd_prefix": "del ",
         "library": "var_list.py",
         "varRefreshCmd": "print(var_dic_list())"
        },
        "r": {
         "delete_cmd_postfix": ") ",
         "delete_cmd_prefix": "rm(",
         "library": "var_list.r",
         "varRefreshCmd": "cat(var_dic_list()) "
        }
       },
    
    Riku-Laine's avatar
    Riku-Laine committed
       "position": {
        "height": "352.85px",
        "left": "1070px",
        "right": "20px",
        "top": "120px",
        "width": "350px"
       },
    
    Riku-Laine's avatar
    Riku-Laine committed
       "types_to_exclude": [
        "module",
        "function",
        "builtin_function_or_method",
        "instance",
        "_Feature"
       ],
       "window_display": false
      }
     },
     "nbformat": 4,
     "nbformat_minor": 2
    }