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628 lines
820 KiB
628 lines
820 KiB
2 years ago
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"___\n",
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"\n",
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"<a href='http://www.pieriandata.com'><img src='../Pierian_Data_Logo.png'/></a>\n",
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"___\n",
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"<center><em>Copyright by Pierian Data Inc.</em></center>\n",
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"<center><em>For more information, visit us at <a href='http://www.pieriandata.com'>www.pieriandata.com</a></em></center>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Introduction to DBSCAN\n",
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"\n",
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"\n",
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"Let's briefly explore visually the differences between DBSCAN and other clustering techniques, such as K-Means Clustering."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## DBSCAN and Clustering Examples"
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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": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns"
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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": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"blobs = pd.read_csv('../DATA/cluster_blobs.csv')"
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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": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>X1</th>\n",
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" <th>X2</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>4.645333</td>\n",
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" <td>6.822294</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>4.784032</td>\n",
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" <td>6.422883</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>-5.851786</td>\n",
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" <td>5.774331</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>-7.459592</td>\n",
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" <td>6.456415</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>4.918911</td>\n",
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" <td>6.961479</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" X1 X2\n",
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"0 4.645333 6.822294\n",
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"1 4.784032 6.422883\n",
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"2 -5.851786 5.774331\n",
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"3 -7.459592 6.456415\n",
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"4 4.918911 6.961479"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"blobs.head()"
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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": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<AxesSubplot:xlabel='X1', ylabel='X2'>"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 432x288 with 1 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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},
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"output_type": "display_data"
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}
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],
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"source": [
|
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"sns.scatterplot(data=blobs,x='X1',y='X2')"
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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": 5,
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"metadata": {},
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"outputs": [],
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"source": [
|
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"moons = pd.read_csv('../DATA/cluster_moons.csv')"
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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": 6,
|
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"metadata": {},
|
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"outputs": [
|
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
|
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
|
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" <th>X1</th>\n",
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" <th>X2</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
|
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" <th>0</th>\n",
|
||
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" <td>0.674362</td>\n",
|
||
|
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" <td>-0.444625</td>\n",
|
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" </tr>\n",
|
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|
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" <tr>\n",
|
||
|
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" <th>1</th>\n",
|
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|
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" <td>1.547129</td>\n",
|
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|
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" <td>-0.239796</td>\n",
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" </tr>\n",
|
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|
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" <tr>\n",
|
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" <th>2</th>\n",
|
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" <td>1.601930</td>\n",
|
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" <td>-0.230792</td>\n",
|
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" </tr>\n",
|
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|
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" <tr>\n",
|
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" <th>3</th>\n",
|
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" <td>0.014563</td>\n",
|
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|
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" <td>0.449752</td>\n",
|
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" </tr>\n",
|
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|
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" <tr>\n",
|
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" <th>4</th>\n",
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" <td>1.503476</td>\n",
|
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|
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" <td>-0.389164</td>\n",
|
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|
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" </tr>\n",
|
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|
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" </tbody>\n",
|
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"</table>\n",
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"</div>"
|
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],
|
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"text/plain": [
|
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" X1 X2\n",
|
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"0 0.674362 -0.444625\n",
|
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"1 1.547129 -0.239796\n",
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"2 1.601930 -0.230792\n",
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"3 0.014563 0.449752\n",
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"4 1.503476 -0.389164"
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]
|
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},
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"execution_count": 6,
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"metadata": {},
|
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"source": [
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|
||
|
|
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||
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{
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}
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],
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"source": [
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"sns.scatterplot(data=moons,x='X1',y='X2')"
|
||
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|
]
|
||
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},
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{
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"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"circles = pd.read_csv('../DATA/cluster_circles.csv')"
|
||
|
|
]
|
||
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},
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{
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"cell_type": "code",
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|
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|
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||
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|
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|
||
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|
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|
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||
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|
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||
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{
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|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"sns.scatterplot(data=circles,x='X1',y='X2')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## Label Discovery"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 11,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"def display_categories(model,data):\n",
|
||
|
|
" labels = model.fit_predict(data)\n",
|
||
|
|
" sns.scatterplot(data=data,x='X1',y='X2',hue=labels,palette='Set1')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## Kmeans Results"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 12,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"from sklearn.cluster import KMeans\n",
|
||
|
|
"model = KMeans(n_clusters = 2)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 27,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"display_categories(model,moons)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 14,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"model = KMeans(n_clusters = 3)\n",
|
||
|
|
"display_categories(model,blobs)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 25,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"model = KMeans(n_clusters = 2)\n",
|
||
|
|
"display_categories(model,circles)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## DBSCAN Results"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 16,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"from sklearn.cluster import DBSCAN"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 17,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"model = DBSCAN(eps=0.6)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 18,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"display_categories(model,blobs)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 28,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1500x900 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"model = DBSCAN(eps=0.15)\n",
|
||
|
|
"plt.figure(figsize=(10,6),dpi=150)\n",
|
||
|
|
"display_categories(model,moons)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 20,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"display_categories(model,circles)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"Let's further explore DBSCAN Hyperparameters!"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"anaconda-cloud": {},
|
||
|
|
"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",
|
||
|
|
"version": "3.8.5"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 1
|
||
|
|
}
|