Create testing.ipynb

Author: Programmer-RD-AI

testing.ipynb

@@ -0,0 +1,118 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "edf5b12f-64d7-43be-8a25-6ed5cea8d0e8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Components: [[-0.57735027 -0.57735027 -0.57735027]\n",
+      " [ 0.          0.          0.        ]]\n",
+      "Transformed data: [[ 5.14470537  0.        ]\n",
+      " [ 0.          0.        ]\n",
+      " [-5.14470537  0.        ]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.decomposition import SparsePCA\n",
+    "import numpy as np\n",
+    "\n",
+    "# Generate example data\n",
+    "X = np.array([[1, 2, 3],\n",
+    "              [4, 5, 6],\n",
+    "              [7, 8, 9]])\n",
+    "\n",
+    "# Perform Sparse PCA\n",
+    "spca = SparsePCA(n_components=2, alpha=1)\n",
+    "X_spca = spca.fit_transform(X)\n",
+    "\n",
+    "# Components\n",
+    "print(\"Components:\", spca.components_)\n",
+    "\n",
+    "# Transformed data\n",
+    "print(\"Transformed data:\", X_spca) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "eb31b678-a661-4764-99c1-cd16429bb3c5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "((3, 2), (3, 3))"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_spca.shape, X.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "66f4a8e0-68ea-441e-9b61-4eb9e6f0c141",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([[ 5.14470537,  0.        ],\n",
+       "        [ 0.        ,  0.        ],\n",
+       "        [-5.14470537,  0.        ]]),\n",
+       " array([[1, 2, 3],\n",
+       "        [4, 5, 6],\n",
+       "        [7, 8, 9]]))"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_spca, X"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "97c79b31-37ae-4f4c-88ae-dcc234346957",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.11.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}