From 5fb4188061b950f62c1cfd8c0fc0a24bf2d4f913 Mon Sep 17 00:00:00 2001 From: Gaurav Rajesh Sahani Date: Fri, 2 Oct 2020 08:35:42 +0530 Subject: [PATCH] Add files via upload --- Unsupervised K-Mean clustering.ipynb | 645 +++++++++++++++++++++++++++ 1 file changed, 645 insertions(+) create mode 100644 Unsupervised K-Mean clustering.ipynb diff --git a/Unsupervised K-Mean clustering.ipynb b/Unsupervised K-Mean clustering.ipynb new file mode 100644 index 0000000..ac9a73d --- /dev/null +++ b/Unsupervised K-Mean clustering.ipynb @@ -0,0 +1,645 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.datasets import make_blobs" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "dataset = make_blobs(n_samples=200,\n", + " centers=4, n_features=2,\n", + " cluster_std=1.6, random_state=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([[ -4.05274874, -4.14693625],\n", + " [ -2.73261956, 5.01059193],\n", + " [ -6.39719898, -6.89759506],\n", + " [ -9.19600485, -10.9703298 ],\n", + " [ -5.82251463, -4.41054135],\n", + " [ -1.15454399, 1.17096792],\n", + " [ -0.83887219, 3.92954133],\n", + " [ -3.44725646, 4.78155499],\n", + " [ -6.47875096, -9.82457112],\n", + " [-10.17442775, -4.94112785],\n", + " [ -2.86659661, 6.41107892],\n", + " [ -8.71473485, -3.87884087],\n", + " [ -6.89492583, -10.59431661],\n", + " [ -9.01647322, -4.23423827],\n", + " [ -6.25343149, -4.20029521],\n", + " [ -5.85079313, -6.737374 ],\n", + " [ -6.45078216, -3.07510715],\n", + " [ -6.91220204, -6.67890799],\n", + " [ -6.99277662, -4.16470232],\n", + " [ -6.67661108, -7.83029982],\n", + " [ -6.6530949 , -1.92428386],\n", + " [ -5.28601892, -3.38346758],\n", + " [ -6.6224833 , -9.32646267],\n", + " [ -1.93544504, 3.0019164 ],\n", + " [ -6.95025857, -2.17565783],\n", + " [ 0.99612358, 5.59376053],\n", + " [ -3.48758902, 3.84754151],\n", + " [ -8.31594088, -8.85324248],\n", + " [ -6.00724972, -5.28577497],\n", + " [ -9.16479036, -5.78429477],\n", + " [-10.03709963, -5.19360714],\n", + " [ -6.60928521, -7.73328019],\n", + " [ -9.04384759, -6.75188582],\n", + " [ -7.58728138, -10.30150937],\n", + " [ -9.59963385, -4.42797439],\n", + " [ -7.76905922, -3.94161798],\n", + " [ -4.16802632, -10.24239118],\n", + " [ -5.68722487, -1.11614675],\n", + " [ -7.2576255 , -10.12622128],\n", + " [-10.28510082, -6.47144773],\n", + " [ -8.90960076, -4.46503111],\n", + " [ -8.60749465, -2.75268992],\n", + " [ -1.40350059, 5.80836014],\n", + " [ -0.21819039, 3.31252529],\n", + " [ -7.06790856, -10.38782078],\n", + " [ -6.85040507, -6.22994033],\n", + " [ 0.67981279, 1.11026473],\n", + " [ -8.85123421, -8.02374474],\n", + " [ -9.29152939, -4.11359692],\n", + " [ -0.2749077 , 0.72402795],\n", + " [ -6.33138445, 0.28818263],\n", + " [ -6.0675027 , -8.8491588 ],\n", + " [ -8.73686497, -3.80541775],\n", + " [ -2.37496561, 6.3657022 ],\n", + " [ -5.72727463, -5.68385353],\n", + " [ -7.93812085, -8.47136869],\n", + " [-11.91654136, -2.57199604],\n", + " [ -8.72922152, -4.95099771],\n", + " [ -6.65550287, -1.24032484],\n", + " [ -1.14909735, 4.00749727],\n", + " [ -1.46730558, 5.39401484],\n", + " [ -8.85546682, -5.02350186],\n", + " [ -7.86738112, -4.41304113],\n", + " [-12.03380651, -3.45167219],\n", + " [ -5.57372962, -1.29306014],\n", + " [ -7.16678733, -1.58611547],\n", + " [ -8.20344417, -3.29910769],\n", + " [ -5.3393612 , -2.56994667],\n", + " [ -7.47156997, -5.9134778 ],\n", + " [ -6.23981523, -3.83866357],\n", + " [ -5.22746753, -3.17068698],\n", + " [ -0.98196894, 4.53023398],\n", + " [ -9.03400166, -3.28089702],\n", + " [ -9.74359548, -6.83318039],\n", + " [ -2.76621711, 3.77168423],\n", + " [ -9.20537439, -4.2328736 ],\n", + " [-10.49389934, -7.84908897],\n", + " [ -3.78300468, -7.2161689 ],\n", + " [ -9.37028382, -6.18162319],\n", + " [ -8.5935626 , -7.21577141],\n", + " [ -5.27991017, -4.04847271],\n", + " [ 0.1544712 , 2.64666384],\n", + " [ -5.28186942, -9.09166641],\n", + " [ -4.57079332, -7.97818379],\n", + " [ -8.33559314, -0.45418111],\n", + " [ -9.38411322, -2.52479448],\n", + " [ -8.14117079, -3.3621602 ],\n", + " [ -1.85618427, 2.90925877],\n", + " [ -7.61686172, -8.52257169],\n", + " [ -8.95659119, -9.21843533],\n", + " [-10.21602409, -4.14383525],\n", + " [ -3.95250896, -4.07764442],\n", + " [ -3.42055059, 6.2380478 ],\n", + " [ -9.54864838, -4.07032887],\n", + " [-10.05962532, -6.53858431],\n", + " [ -1.20262019, 5.82271573],\n", + " [-11.0327792 , -2.51096952],\n", + " [ -6.98236262, -2.57114169],\n", + " [ -8.64385547, -5.32857405],\n", + " [ -4.91046927, -3.0322093 ],\n", + " [-10.82506364, -5.54859147],\n", + " [ -5.95239137, -4.35116419],\n", + " [ -6.93341843, -1.04314053],\n", + " [ 0.15104711, 6.83819678],\n", + " [ -9.27185334, -1.61580127],\n", + " [ -4.47733631, -2.60035819],\n", + " [ -9.70603621, -9.57811704],\n", + " [ -7.95970302, -0.80598575],\n", + " [ -8.44298836, -7.07368966],\n", + " [ -1.17928739, 3.84289011],\n", + " [-10.28718499, -4.91962155],\n", + " [ -5.45067799, -7.54084061],\n", + " [ -2.17542743, 3.7920029 ],\n", + " [ -0.21701475, 5.21048081],\n", + " [ -9.09729475, -3.5681692 ],\n", + " [ -2.26001583, 3.38452122],\n", + " [ -2.20972579, 4.47624484],\n", + " [ -7.87002745, -3.25965584],\n", + " [ -1.35409513, 7.76689809],\n", + " [ -9.8731987 , -2.96394013],\n", + " [ -8.94323283, -6.55724989],\n", + " [-11.53381818, -5.053182 ],\n", + " [ -8.4195762 , -3.61169431],\n", + " [ -7.03539237, -2.32460917],\n", + " [ -4.65859229, -1.61675677],\n", + " [ -0.87793087, 4.28557513],\n", + " [ -8.81282218, -5.47926951],\n", + " [ -7.39694685, -3.9483423 ],\n", + " [ -6.72135213, -0.49222692],\n", + " [ -4.90954582, -3.74963235],\n", + " [ 0.2587087 , 4.70274014],\n", + " [-11.74957146, -3.68233665],\n", + " [ -6.27714369, -9.24231313],\n", + " [ -1.59201791, 5.33899421],\n", + " [ 1.83736074, 2.17209573],\n", + " [ -3.75962887, -10.50707919],\n", + " [ -7.20009503, -8.62900712],\n", + " [ -7.03843808, -7.86972775],\n", + " [ -1.29140833, 5.62570776],\n", + " [ -2.73355372, 4.38622651],\n", + " [ -5.53693321, -4.97035773],\n", + " [-10.63911761, -2.63493956],\n", + " [ -8.36525029, -2.96657669],\n", + " [ -1.96649679, 2.98628353],\n", + " [ -8.18551979, -8.47865922],\n", + " [ -6.96768187, -7.8154285 ],\n", + " [ -7.43575116, -4.47721534],\n", + " [ -6.46037207, -3.36951981],\n", + " [ 1.13213892, 3.18855883],\n", + " [ -3.33924757, -2.18577289],\n", + " [ -8.39315722, -9.56215226],\n", + " [ -2.65156126, 5.52334112],\n", + " [ -1.46464587, 6.21366412],\n", + " [-11.96580552, -3.07248855],\n", + " [ -2.85501318, 7.11441723],\n", + " [ -9.1926168 , -1.88418714],\n", + " [ -6.49235949, -4.36441712],\n", + " [ -2.01528493, 4.08527696],\n", + " [-10.42366211, -3.90116527],\n", + " [ -1.5782675 , 3.38729683],\n", + " [ -2.85427086, -4.34563985],\n", + " [ -9.15056798, -3.73302661],\n", + " [-12.97048349, -1.9754861 ],\n", + " [ -1.34228035, 4.5969037 ],\n", + " [ -7.36340857, -8.24414727],\n", + " [ -9.53431773, -6.19692815],\n", + " [ -9.43683894, -6.05300201],\n", + " [ -8.55728445, -0.26004954],\n", + " [ -5.79284043, -8.75232941],\n", + " [ -1.99379068, 5.34508697],\n", + " [-10.89740119, -0.82554363],\n", + " [ -6.02477361, -3.3931391 ],\n", + " [ -6.37764036, -9.12442554],\n", + " [ -6.49259294, -6.98752602],\n", + " [ -0.31718644, 5.8962532 ],\n", + " [ -7.90981328, -1.81754028],\n", + " [ -2.08818083, 5.25505862],\n", + " [ -2.14948633, 5.7312493 ],\n", + " [ -9.92784211, -4.31545134],\n", + " [ -7.3934713 , -3.41252983],\n", + " [ -6.54391392, -3.36747401],\n", + " [ -9.96985745, -5.74857851],\n", + " [ -2.75903623, 3.05416084],\n", + " [ -3.97014199, 3.59934449],\n", + " [ -8.46853261, -9.54168766],\n", + " [ -8.70018983, -2.2822412 ],\n", + " [ -5.28106345, -1.55899073],\n", + " [ -1.36106168, 5.0625725 ],\n", + " [-10.29622414, -4.11614194],\n", + " [ -9.62572121, -2.8612663 ],\n", + " [ -7.40414058, -1.18048775],\n", + " [ -1.42542439, -1.76945006],\n", + " [ -6.58688752, -1.80015598],\n", + " [ -4.81281818, -7.94666558],\n", + " [ -1.01397328, 5.35621551],\n", + " [ -7.86202389, -8.65080407],\n", + " [ -6.07521957, -8.86230319],\n", + " [-12.19470022, -3.44909352],\n", + " [ -9.0842768 , -1.9451221 ],\n", + " [ -4.47776283, -7.34884269]]),\n", + " array([3, 0, 2, 2, 3, 0, 0, 0, 2, 1, 0, 1, 2, 2, 3, 2, 3, 2, 3, 2, 3, 3,\n", + " 2, 0, 1, 0, 0, 2, 2, 1, 1, 2, 2, 2, 1, 3, 2, 3, 2, 3, 1, 1, 0, 0,\n", + " 2, 2, 0, 2, 1, 0, 3, 2, 3, 0, 2, 2, 1, 1, 3, 0, 0, 2, 1, 1, 3, 3,\n", + " 1, 3, 2, 3, 3, 0, 1, 2, 0, 1, 1, 2, 2, 2, 3, 0, 2, 2, 1, 3, 1, 0,\n", + " 2, 2, 1, 3, 0, 1, 1, 0, 1, 3, 1, 3, 1, 1, 3, 0, 3, 3, 2, 1, 2, 0,\n", + " 1, 3, 0, 0, 1, 0, 0, 3, 0, 1, 1, 2, 1, 3, 3, 0, 1, 3, 3, 3, 0, 1,\n", + " 2, 0, 0, 2, 2, 2, 0, 0, 3, 1, 3, 0, 2, 2, 3, 3, 0, 3, 2, 0, 0, 1,\n", + " 0, 1, 3, 0, 1, 0, 3, 1, 1, 0, 2, 3, 1, 3, 2, 0, 1, 3, 2, 1, 0, 3,\n", + " 0, 0, 1, 1, 3, 1, 0, 0, 2, 1, 3, 0, 1, 1, 3, 3, 3, 2, 0, 2, 2, 1,\n", + " 3, 2]))" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "df = dataset[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ -4.05274874, -4.14693625],\n", + " [ -2.73261956, 5.01059193],\n", + " [ -6.39719898, -6.89759506],\n", + " [ -9.19600485, -10.9703298 ],\n", + " [ -5.82251463, -4.41054135],\n", + " [ -1.15454399, 1.17096792],\n", + " [ -0.83887219, 3.92954133],\n", + " [ -3.44725646, 4.78155499],\n", + " [ -6.47875096, -9.82457112],\n", + " [-10.17442775, -4.94112785],\n", + " [ -2.86659661, 6.41107892],\n", + " [ -8.71473485, -3.87884087],\n", + " [ -6.89492583, -10.59431661],\n", + " [ -9.01647322, -4.23423827],\n", + " [ -6.25343149, -4.20029521],\n", + " [ -5.85079313, -6.737374 ],\n", + " [ -6.45078216, -3.07510715],\n", + " [ -6.91220204, -6.67890799],\n", + " [ -6.99277662, -4.16470232],\n", + " [ -6.67661108, -7.83029982],\n", + " [ -6.6530949 , -1.92428386],\n", + " [ -5.28601892, -3.38346758],\n", + " [ -6.6224833 , -9.32646267],\n", + " [ -1.93544504, 3.0019164 ],\n", + " [ -6.95025857, -2.17565783],\n", + " [ 0.99612358, 5.59376053],\n", + " [ -3.48758902, 3.84754151],\n", + " [ -8.31594088, -8.85324248],\n", + " [ -6.00724972, -5.28577497],\n", + " [ -9.16479036, -5.78429477],\n", + " [-10.03709963, -5.19360714],\n", + " [ -6.60928521, -7.73328019],\n", + " [ -9.04384759, -6.75188582],\n", + " [ -7.58728138, -10.30150937],\n", + " [ -9.59963385, -4.42797439],\n", + " [ -7.76905922, -3.94161798],\n", + " [ -4.16802632, -10.24239118],\n", + " [ -5.68722487, -1.11614675],\n", + " [ -7.2576255 , -10.12622128],\n", + " [-10.28510082, -6.47144773],\n", + " [ -8.90960076, -4.46503111],\n", + " [ -8.60749465, -2.75268992],\n", + " [ -1.40350059, 5.80836014],\n", + " [ -0.21819039, 3.31252529],\n", + " [ -7.06790856, -10.38782078],\n", + " [ -6.85040507, -6.22994033],\n", + " [ 0.67981279, 1.11026473],\n", + " [ -8.85123421, -8.02374474],\n", + " [ -9.29152939, -4.11359692],\n", + " [ -0.2749077 , 0.72402795],\n", + " [ -6.33138445, 0.28818263],\n", + " [ -6.0675027 , -8.8491588 ],\n", + " [ -8.73686497, -3.80541775],\n", + " [ -2.37496561, 6.3657022 ],\n", + " [ -5.72727463, -5.68385353],\n", + " [ -7.93812085, -8.47136869],\n", + " [-11.91654136, -2.57199604],\n", + " [ -8.72922152, -4.95099771],\n", + " [ -6.65550287, -1.24032484],\n", + " [ -1.14909735, 4.00749727],\n", + " [ -1.46730558, 5.39401484],\n", + " [ -8.85546682, -5.02350186],\n", + " [ -7.86738112, -4.41304113],\n", + " [-12.03380651, -3.45167219],\n", + " [ -5.57372962, -1.29306014],\n", + " [ -7.16678733, -1.58611547],\n", + " [ -8.20344417, -3.29910769],\n", + " [ -5.3393612 , -2.56994667],\n", + " [ -7.47156997, -5.9134778 ],\n", + " [ -6.23981523, -3.83866357],\n", + " [ -5.22746753, -3.17068698],\n", + " [ -0.98196894, 4.53023398],\n", + " [ -9.03400166, -3.28089702],\n", + " [ -9.74359548, -6.83318039],\n", + " [ -2.76621711, 3.77168423],\n", + " [ -9.20537439, -4.2328736 ],\n", + " [-10.49389934, -7.84908897],\n", + " [ -3.78300468, -7.2161689 ],\n", + " [ -9.37028382, -6.18162319],\n", + " [ -8.5935626 , -7.21577141],\n", + " [ -5.27991017, -4.04847271],\n", + " [ 0.1544712 , 2.64666384],\n", + " [ -5.28186942, -9.09166641],\n", + " [ -4.57079332, -7.97818379],\n", + " [ -8.33559314, -0.45418111],\n", + " [ -9.38411322, -2.52479448],\n", + " [ -8.14117079, -3.3621602 ],\n", + " [ -1.85618427, 2.90925877],\n", + " [ -7.61686172, -8.52257169],\n", + " [ -8.95659119, -9.21843533],\n", + " [-10.21602409, -4.14383525],\n", + " [ -3.95250896, -4.07764442],\n", + " [ -3.42055059, 6.2380478 ],\n", + " [ -9.54864838, -4.07032887],\n", + " [-10.05962532, -6.53858431],\n", + " [ -1.20262019, 5.82271573],\n", + " [-11.0327792 , -2.51096952],\n", + " [ -6.98236262, -2.57114169],\n", + " [ -8.64385547, -5.32857405],\n", + " [ -4.91046927, -3.0322093 ],\n", + " [-10.82506364, -5.54859147],\n", + " [ -5.95239137, -4.35116419],\n", + " [ -6.93341843, -1.04314053],\n", + " [ 0.15104711, 6.83819678],\n", + " [ -9.27185334, -1.61580127],\n", + " [ -4.47733631, -2.60035819],\n", + " [ -9.70603621, -9.57811704],\n", + " [ -7.95970302, -0.80598575],\n", + " [ -8.44298836, -7.07368966],\n", + " [ -1.17928739, 3.84289011],\n", + " [-10.28718499, -4.91962155],\n", + " [ -5.45067799, -7.54084061],\n", + " [ -2.17542743, 3.7920029 ],\n", + " [ -0.21701475, 5.21048081],\n", + " [ -9.09729475, -3.5681692 ],\n", + " [ -2.26001583, 3.38452122],\n", + " [ -2.20972579, 4.47624484],\n", + " [ -7.87002745, -3.25965584],\n", + " [ -1.35409513, 7.76689809],\n", + " [ -9.8731987 , -2.96394013],\n", + " [ -8.94323283, -6.55724989],\n", + " [-11.53381818, -5.053182 ],\n", + " [ -8.4195762 , -3.61169431],\n", + " [ -7.03539237, -2.32460917],\n", + " [ -4.65859229, -1.61675677],\n", + " [ -0.87793087, 4.28557513],\n", + " [ -8.81282218, -5.47926951],\n", + " [ -7.39694685, -3.9483423 ],\n", + " [ -6.72135213, -0.49222692],\n", + " [ -4.90954582, -3.74963235],\n", + " [ 0.2587087 , 4.70274014],\n", + " [-11.74957146, -3.68233665],\n", + " [ -6.27714369, -9.24231313],\n", + " [ -1.59201791, 5.33899421],\n", + " [ 1.83736074, 2.17209573],\n", + " [ -3.75962887, -10.50707919],\n", + " [ -7.20009503, -8.62900712],\n", + " [ -7.03843808, -7.86972775],\n", + " [ -1.29140833, 5.62570776],\n", + " [ -2.73355372, 4.38622651],\n", + " [ -5.53693321, -4.97035773],\n", + " [-10.63911761, -2.63493956],\n", + " [ -8.36525029, -2.96657669],\n", + " [ -1.96649679, 2.98628353],\n", + " [ -8.18551979, -8.47865922],\n", + " [ -6.96768187, -7.8154285 ],\n", + " [ -7.43575116, -4.47721534],\n", + " [ -6.46037207, -3.36951981],\n", + " [ 1.13213892, 3.18855883],\n", + " [ -3.33924757, -2.18577289],\n", + " [ -8.39315722, -9.56215226],\n", + " [ -2.65156126, 5.52334112],\n", + " [ -1.46464587, 6.21366412],\n", + " [-11.96580552, -3.07248855],\n", + " [ -2.85501318, 7.11441723],\n", + " [ -9.1926168 , -1.88418714],\n", + " [ -6.49235949, -4.36441712],\n", + " [ -2.01528493, 4.08527696],\n", + " [-10.42366211, -3.90116527],\n", + " [ -1.5782675 , 3.38729683],\n", + " [ -2.85427086, -4.34563985],\n", + " [ -9.15056798, -3.73302661],\n", + " [-12.97048349, -1.9754861 ],\n", + " [ -1.34228035, 4.5969037 ],\n", + " [ -7.36340857, -8.24414727],\n", + " [ -9.53431773, -6.19692815],\n", + " [ -9.43683894, -6.05300201],\n", + " [ -8.55728445, -0.26004954],\n", + " [ -5.79284043, -8.75232941],\n", + " [ -1.99379068, 5.34508697],\n", + " [-10.89740119, -0.82554363],\n", + " [ -6.02477361, -3.3931391 ],\n", + " [ -6.37764036, -9.12442554],\n", + " [ -6.49259294, -6.98752602],\n", + " [ -0.31718644, 5.8962532 ],\n", + " [ -7.90981328, -1.81754028],\n", + " [ -2.08818083, 5.25505862],\n", + " [ -2.14948633, 5.7312493 ],\n", + " [ -9.92784211, -4.31545134],\n", + " [ -7.3934713 , -3.41252983],\n", + " [ -6.54391392, -3.36747401],\n", + " [ -9.96985745, -5.74857851],\n", + " [ -2.75903623, 3.05416084],\n", + " [ -3.97014199, 3.59934449],\n", + " [ -8.46853261, -9.54168766],\n", + " [ -8.70018983, -2.2822412 ],\n", + " [ -5.28106345, -1.55899073],\n", + " [ -1.36106168, 5.0625725 ],\n", + " [-10.29622414, -4.11614194],\n", + " [ -9.62572121, -2.8612663 ],\n", + " [ -7.40414058, -1.18048775],\n", + " [ -1.42542439, -1.76945006],\n", + " [ -6.58688752, -1.80015598],\n", + " [ -4.81281818, -7.94666558],\n", + " [ -1.01397328, 5.35621551],\n", + " [ -7.86202389, -8.65080407],\n", + " [ -6.07521957, -8.86230319],\n", + " [-12.19470022, -3.44909352],\n", + " [ -9.0842768 , -1.9451221 ],\n", + " [ -4.47776283, -7.34884269]])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.cluster import KMeans" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "kmeans = KMeans(n_clusters=4)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\n", + " n_clusters=4, n_init=10, n_jobs=None, precompute_distances='auto',\n", + " random_state=None, tol=0.0001, verbose=0)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "kmeans.fit(df)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(dataset[0][:,0], dataset[0][:,1])" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[-1.47571305 4.49212417]\n", + " [-6.06330584 -2.78386756]\n", + " [-6.97170668 -8.46938111]\n", + " [-9.70501129 -4.06587709]]\n" + ] + } + ], + "source": [ + "cluster = kmeans.cluster_centers_\n", + "print(cluster)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "y_km = kmeans.fit_predict(df)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(df[y_km == 0,0], df[y_km == 0,1], s=60, color='blue')\n", + "plt.scatter(df[y_km == 1,0], df[y_km == 1,1], s=60, color='red')\n", + "plt.scatter(df[y_km == 2,0], df[y_km == 2,1], s=60, color='green')\n", + "plt.scatter(df[y_km == 3,0], df[y_km == 3,1], s=60, color='orange')\n", + "\n", + "plt.scatter(cluster[0][0], cluster[0][1], marker='*', s=200, color='black')\n", + "plt.scatter(cluster[1][0], cluster[1][1], marker='*', s=200, color='black')\n", + "plt.scatter(cluster[2][0], cluster[2][1], marker='*', s=200, color='black')\n", + "plt.scatter(cluster[3][0], cluster[3][1], marker='*', s=200, color='black')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "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": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}