111 lines
2.5 KiB
Plaintext
111 lines
2.5 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Importing the libraries\n",
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"import numpy as np\n",
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"import pandas as pd"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Importing the dataset\n",
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"dataset = pd.read_csv('Credit_Card_Applications.csv')\n",
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"X = dataset.iloc[:, :-1].values\n",
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"y = dataset.iloc[:, -1].values"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Feature Scaling\n",
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"from sklearn.preprocessing import MinMaxScaler\n",
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"sc = MinMaxScaler(feature_range = (0, 1))\n",
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"X = sc.fit_transform(X)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Training the SOM\n",
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"from minisom import MiniSom\n",
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"som = MiniSom(x = 10, y = 10, input_len = 15, sigma = 1.0, learning_rate = 0.5)\n",
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"som.random_weights_init(X)\n",
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"som.train_random(data = X, num_iteration = 100)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Visualizing the results\n",
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"from pylab import bone, pcolor, colorbar, plot, show\n",
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"bone()\n",
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"pcolor(som.distance_map().T)\n",
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"colorbar()\n",
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"markers = ['o', 's']\n",
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"colors = ['r', 'g']\n",
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"for i, x in enumerate(X):\n",
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" w = som.winner(x)\n",
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" plot(w[0] + 0.5,\n",
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" w[1] + 0.5,\n",
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" markers[y[i]],\n",
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" markeredgecolor = colors[y[i]],\n",
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" markerfacecolor = 'None',\n",
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" markersize = 10,\n",
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" markeredgewidth = 2)\n",
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"show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Finding the frauds\n",
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"mappings = som.win_map(X)\n",
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"frauds = np.concatenate((mappings[(8,8)], mappings[(2,6)]), axis = 0)\n",
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"frauds = sc.inverse_transform(frauds)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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