migrate from github

app.py

@@ -8,7 +8,7 @@ from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_sc
 from sklearn.model_selection import train_test_split
 
 # Load
-train_df = pd.read_csv("Titanic-Survival/datasets/train.csv")
+train_df = pd.read_csv("datasets/train.csv")
 
 # Preprocess
 train_df["Age"].fillna(train_df["Age"].median(), inplace=True)

notebook.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -28,7 +28,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -48,7 +48,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -60,13 +60,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<style>#sk-container-id-4 {\n",
+       "<style>#sk-container-id-1 {\n",
        "  /* Definition of color scheme common for light and dark mode */\n",
        "  --sklearn-color-text: #000;\n",
        "  --sklearn-color-text-muted: #666;\n",
@@ -97,15 +97,15 @@
        "  }\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 {\n",
+       "#sk-container-id-1 {\n",
        "  color: var(--sklearn-color-text);\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 pre {\n",
+       "#sk-container-id-1 pre {\n",
        "  padding: 0;\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 input.sk-hidden--visually {\n",
+       "#sk-container-id-1 input.sk-hidden--visually {\n",
        "  border: 0;\n",
        "  clip: rect(1px 1px 1px 1px);\n",
        "  clip: rect(1px, 1px, 1px, 1px);\n",
@@ -117,7 +117,7 @@
        "  width: 1px;\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-dashed-wrapped {\n",
+       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
        "  border: 1px dashed var(--sklearn-color-line);\n",
        "  margin: 0 0.4em 0.5em 0.4em;\n",
        "  box-sizing: border-box;\n",
@@ -125,7 +125,7 @@
        "  background-color: var(--sklearn-color-background);\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-container {\n",
+       "#sk-container-id-1 div.sk-container {\n",
        "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
        "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
        "     so we also need the `!important` here to be able to override the\n",
@@ -135,7 +135,7 @@
        "  position: relative;\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-text-repr-fallback {\n",
+       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
        "  display: none;\n",
        "}\n",
        "\n",
@@ -151,14 +151,14 @@
        "\n",
        "/* Parallel-specific style estimator block */\n",
        "\n",
-       "#sk-container-id-4 div.sk-parallel-item::after {\n",
+       "#sk-container-id-1 div.sk-parallel-item::after {\n",
        "  content: \"\";\n",
        "  width: 100%;\n",
        "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
        "  flex-grow: 1;\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-parallel {\n",
+       "#sk-container-id-1 div.sk-parallel {\n",
        "  display: flex;\n",
        "  align-items: stretch;\n",
        "  justify-content: center;\n",
@@ -166,28 +166,28 @@
        "  position: relative;\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-parallel-item {\n",
+       "#sk-container-id-1 div.sk-parallel-item {\n",
        "  display: flex;\n",
        "  flex-direction: column;\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-parallel-item:first-child::after {\n",
+       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
        "  align-self: flex-end;\n",
        "  width: 50%;\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-parallel-item:last-child::after {\n",
+       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
        "  align-self: flex-start;\n",
        "  width: 50%;\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-parallel-item:only-child::after {\n",
+       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
        "  width: 0;\n",
        "}\n",
        "\n",
        "/* Serial-specific style estimator block */\n",
        "\n",
-       "#sk-container-id-4 div.sk-serial {\n",
+       "#sk-container-id-1 div.sk-serial {\n",
        "  display: flex;\n",
        "  flex-direction: column;\n",
        "  align-items: center;\n",
@@ -205,14 +205,14 @@
        "\n",
        "/* Pipeline and ColumnTransformer style (default) */\n",
        "\n",
-       "#sk-container-id-4 div.sk-toggleable {\n",
+       "#sk-container-id-1 div.sk-toggleable {\n",
        "  /* Default theme specific background. It is overwritten whether we have a\n",
        "  specific estimator or a Pipeline/ColumnTransformer */\n",
        "  background-color: var(--sklearn-color-background);\n",
        "}\n",
        "\n",
        "/* Toggleable label */\n",
-       "#sk-container-id-4 label.sk-toggleable__label {\n",
+       "#sk-container-id-1 label.sk-toggleable__label {\n",
        "  cursor: pointer;\n",
        "  display: flex;\n",
        "  width: 100%;\n",
@@ -225,13 +225,13 @@
        "  gap: 0.5em;\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 label.sk-toggleable__label .caption {\n",
+       "#sk-container-id-1 label.sk-toggleable__label .caption {\n",
        "  font-size: 0.6rem;\n",
        "  font-weight: lighter;\n",
        "  color: var(--sklearn-color-text-muted);\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 label.sk-toggleable__label-arrow:before {\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
        "  /* Arrow on the left of the label */\n",
        "  content: \"▸\";\n",
        "  float: left;\n",
@@ -239,13 +239,13 @@
        "  color: var(--sklearn-color-icon);\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
        "  color: var(--sklearn-color-text);\n",
        "}\n",
        "\n",
        "/* Toggleable content - dropdown */\n",
        "\n",
-       "#sk-container-id-4 div.sk-toggleable__content {\n",
+       "#sk-container-id-1 div.sk-toggleable__content {\n",
        "  max-height: 0;\n",
        "  max-width: 0;\n",
        "  overflow: hidden;\n",
@@ -254,12 +254,12 @@
        "  background-color: var(--sklearn-color-unfitted-level-0);\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-toggleable__content.fitted {\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
        "  /* fitted */\n",
        "  background-color: var(--sklearn-color-fitted-level-0);\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-toggleable__content pre {\n",
+       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
        "  margin: 0.2em;\n",
        "  border-radius: 0.25em;\n",
        "  color: var(--sklearn-color-text);\n",
@@ -267,79 +267,79 @@
        "  background-color: var(--sklearn-color-unfitted-level-0);\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-toggleable__content.fitted pre {\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
        "  /* unfitted */\n",
        "  background-color: var(--sklearn-color-fitted-level-0);\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
        "  /* Expand drop-down */\n",
        "  max-height: 200px;\n",
        "  max-width: 100%;\n",
        "  overflow: auto;\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
        "  content: \"▾\";\n",
        "}\n",
        "\n",
        "/* Pipeline/ColumnTransformer-specific style */\n",
        "\n",
-       "#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
        "  color: var(--sklearn-color-text);\n",
        "  background-color: var(--sklearn-color-unfitted-level-2);\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
        "  background-color: var(--sklearn-color-fitted-level-2);\n",
        "}\n",
        "\n",
        "/* Estimator-specific style */\n",
        "\n",
        "/* Colorize estimator box */\n",
-       "#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
        "  /* unfitted */\n",
        "  background-color: var(--sklearn-color-unfitted-level-2);\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
        "  /* fitted */\n",
        "  background-color: var(--sklearn-color-fitted-level-2);\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-label label.sk-toggleable__label,\n",
-       "#sk-container-id-4 div.sk-label label {\n",
+       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-1 div.sk-label label {\n",
        "  /* The background is the default theme color */\n",
        "  color: var(--sklearn-color-text-on-default-background);\n",
        "}\n",
        "\n",
        "/* On hover, darken the color of the background */\n",
-       "#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {\n",
+       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
        "  color: var(--sklearn-color-text);\n",
        "  background-color: var(--sklearn-color-unfitted-level-2);\n",
        "}\n",
        "\n",
        "/* Label box, darken color on hover, fitted */\n",
-       "#sk-container-id-4 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
        "  color: var(--sklearn-color-text);\n",
        "  background-color: var(--sklearn-color-fitted-level-2);\n",
        "}\n",
        "\n",
        "/* Estimator label */\n",
        "\n",
-       "#sk-container-id-4 div.sk-label label {\n",
+       "#sk-container-id-1 div.sk-label label {\n",
        "  font-family: monospace;\n",
        "  font-weight: bold;\n",
        "  display: inline-block;\n",
        "  line-height: 1.2em;\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-label-container {\n",
+       "#sk-container-id-1 div.sk-label-container {\n",
        "  text-align: center;\n",
        "}\n",
        "\n",
        "/* Estimator-specific */\n",
-       "#sk-container-id-4 div.sk-estimator {\n",
+       "#sk-container-id-1 div.sk-estimator {\n",
        "  font-family: monospace;\n",
        "  border: 1px dotted var(--sklearn-color-border-box);\n",
        "  border-radius: 0.25em;\n",
@@ -349,18 +349,18 @@
        "  background-color: var(--sklearn-color-unfitted-level-0);\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-estimator.fitted {\n",
+       "#sk-container-id-1 div.sk-estimator.fitted {\n",
        "  /* fitted */\n",
        "  background-color: var(--sklearn-color-fitted-level-0);\n",
        "}\n",
        "\n",
        "/* on hover */\n",
-       "#sk-container-id-4 div.sk-estimator:hover {\n",
+       "#sk-container-id-1 div.sk-estimator:hover {\n",
        "  /* unfitted */\n",
        "  background-color: var(--sklearn-color-unfitted-level-2);\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 div.sk-estimator.fitted:hover {\n",
+       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
        "  /* fitted */\n",
        "  background-color: var(--sklearn-color-fitted-level-2);\n",
        "}\n",
@@ -448,7 +448,7 @@
        "\n",
        "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
        "\n",
-       "#sk-container-id-4 a.estimator_doc_link {\n",
+       "#sk-container-id-1 a.estimator_doc_link {\n",
        "  float: right;\n",
        "  font-size: 1rem;\n",
        "  line-height: 1em;\n",
@@ -463,31 +463,31 @@
        "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 a.estimator_doc_link.fitted {\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
        "  /* fitted */\n",
        "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
        "  color: var(--sklearn-color-fitted-level-1);\n",
        "}\n",
        "\n",
        "/* On hover */\n",
-       "#sk-container-id-4 a.estimator_doc_link:hover {\n",
+       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
        "  /* unfitted */\n",
        "  background-color: var(--sklearn-color-unfitted-level-3);\n",
        "  color: var(--sklearn-color-background);\n",
        "  text-decoration: none;\n",
        "}\n",
        "\n",
-       "#sk-container-id-4 a.estimator_doc_link.fitted:hover {\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
        "  /* fitted */\n",
        "  background-color: var(--sklearn-color-fitted-level-3);\n",
        "}\n",
-       "</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestClassifier(random_state=1)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" checked><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>RandomForestClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.ensemble.RandomForestClassifier.html\">?<span>Documentation for RandomForestClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestClassifier(random_state=1)</pre></div> </div></div></div></div>"
+       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestClassifier(random_state=1)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>RandomForestClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.ensemble.RandomForestClassifier.html\">?<span>Documentation for RandomForestClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestClassifier(random_state=1)</pre></div> </div></div></div></div>"
       ],
       "text/plain": [
        "RandomForestClassifier(random_state=1)"
       ]
      },
-     "execution_count": 36,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -500,7 +500,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -525,7 +525,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]