Did stuff - machinelearning - Unnamed repository; edit this file 'description' to name the repository.

commit b63419c7af4257dbbf9c8b3516173ad5445c08c0
parent acc144969426f9bacd514fd9e44a99564e0243f4
Author: Andrew <andrewlaack1@gmail.com>
Date:   Sun,  7 Jul 2024 23:27:40 -0500

Did stuff

Diffstat:
A mnist/MNISTSNESVD.ipynb  | 643 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

1 file changed, 643 insertions(+), 0 deletions(-)
diff --git a/mnist/MNISTSNESVD.ipynb b/mnist/MNISTSNESVD.ipynb
@@ -0,0 +1,643 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is based off of a concept I found here whereby they used dimensionallity reduction to get 97% accuracy using only a singular decision tree:\n",
+    "\n",
+    "https://www.kaggle.com/code/carlolepelaars/97-on-mnist-with-a-single-decision-tree-t-sne"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "While this is beautiful it is also stupid. While tsne is unsupervised it does not train a model that can transform future data by nature of how it works. This contrasts with SVD and PCA which are built to function in such a way. So while it is cool that it retains relations between values it is also un-usable for inference."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.datasets import fetch_openml\n",
+    "import numpy as np\n",
+    "\n",
+    "np.random.seed(10)\n",
+    "\n",
+    "mnist = fetch_openml(\"mnist_784\", as_frame=False)\n",
+    "y = mnist.target\n",
+    "X = mnist.data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(70000, 784)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.decomposition import TruncatedSVD\n",
+    "\n",
+    "tsvd = TruncatedSVD(n_components=50)\n",
+    "X = tsvd.fit_transform(X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.manifold import TSNE\n",
+    "\n",
+    "tsne = TSNE()\n",
+    "X = tsne.fit_transform(X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[-37.690044 ,   1.8971176],\n",
+       "       [-73.04463  ,  34.260235 ],\n",
+       "       [-26.243597 , -85.17721  ],\n",
+       "       ...,\n",
+       "       [ 27.730738 , -80.13519  ],\n",
+       "       [-19.186428 , -20.6604   ],\n",
+       "       [-72.765045 , -31.39531  ]], dtype=float32)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7ffa7550d510>"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt \n",
+    "\n",
+    "count = 0\n",
+    "while count < len(y):\n",
+    "    y[count] = int(y[count])\n",
+    "    count += 1\n",
+    "\n",
+    "plt.scatter(X[:,0],X[:,1], c=y, cmap='jet', s=2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "\n",
+    "\n",
+    "count = 0\n",
+    "while count < len(y):\n",
+    "    y[count] = str(y[count])\n",
+    "    count += 1\n",
+    "\n",
+    "X_train , X_test, y_train, y_test = train_test_split(X, y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-1 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\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",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\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",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\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",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\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-1 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\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-1 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\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-1 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\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-1 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\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",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\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-1 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\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-1 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\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-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-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-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-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-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-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-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-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-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-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-1 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\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",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\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-1 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-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",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-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",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\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-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-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-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(max_depth=10)</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 fitted\">&nbsp;&nbsp;DecisionTreeClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(max_depth=10)</pre></div> </div></div></div></div>"
+      ],
+      "text/plain": [
+       "DecisionTreeClassifier(max_depth=10)"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.tree import DecisionTreeClassifier\n",
+    "\n",
+    "dclf = DecisionTreeClassifier(max_depth=10)\n",
+    "\n",
+    "dclf.fit(X_train,y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds = dclf.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.9709714285714286"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import accuracy_score\n",
+    "\n",
+    "accuracy_score(y_pred=preds, y_true=y_test)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "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",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

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