How to find the optimal value of K in KNN? | by Amey Band | Towards ...
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How to find the optimal value of K in KNN? | by Amey Band | Towards ...
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How to find the optimal value of K in KNN? | by Amey Band | Towards ...
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How to find the optimal value of K in KNN? | by Amey Band | Towards ...
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How to find the optimal value of K in KNN? | by Amey Band | Towards ...
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How to find the optimal value of K in KNN? | by Amey Band | Towards ...
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How to find the optimal value of K in KNN? | by Amey Band | Towards ...
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How to find the optimal value of K in KNN? | by Amey Band | Towards ...
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib.ticker import NullFormatter
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import pandas as pd
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import matplotlib.ticker as ticker
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%matplotlib inline
https://towardsdatascience.com/how-to-find-the-optimal-value-of-k-in-k...
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df = pd.read_csv('Telecustomers.csv')
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df.head()
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2/7/2021, 11:51 AM
How to find the optimal value of K in KNN? | by Amey Band | Towards ...
https://towardsdatascience.com/how-to-find-the-optimal-value-of-k-in-k...
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X = df.drop(['custcat'], axis = 1)
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y = df['custcat']
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from sklearn import preprocessing
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X = preprocessing.StandardScaler().fit(X).transform(X.astype(float))
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from sklearn.model_selection import train_test_split
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X_train, X_test, y_train, y_test = train_test_split( X, y, test_size=0.2, random_state=4)
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from sklearn.neighbors import KNeighborsClassifier
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from sklearn import metrics
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#Train Model and Predict
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k = 4
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neigh = KNeighborsClassifier(n_neighbors = k).fit(X_train,y_train)
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Pred_y = neigh.predict(X_test)
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print("Accuracy of model at K=4 is",metrics.accuracy_score(y_test, Pred_y))
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How to find the optimal value of K in KNN? | by Amey Band | Towards ...
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error_rate = []
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for i in range(1,40):
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knn = KNeighborsClassifier(n_neighbors=i)
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knn.fit(X_train,y_train)
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pred_i = knn.predict(X_test)
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error_rate.append(np.mean(pred_i != y_test))
https://towardsdatascience.com/how-to-find-the-optimal-value-of-k-in-k...
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plt.figure(figsize=(10,6))
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plt.plot(range(1,40),error_rate,color='blue', linestyle='dashed',
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marker='o',markerfacecolor='red', markersize=10)
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plt.title('Error Rate vs. K Value')
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plt.xlabel('K')
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plt.ylabel('Error Rate')
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print("Minimum error:‐",min(error_rate),"at K =",error_rate.index(min(error_rate)))
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How to find the optimal value of K in KNN? | by Amey Band | Towards ...
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acc = []
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# Will take some time
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from sklearn import metrics
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for i in range(1,40):
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neigh = KNeighborsClassifier(n_neighbors = i).fit(X_train,y_train)
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yhat = neigh.predict(X_test)
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acc.append(metrics.accuracy_score(y_test, yhat))
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plt.figure(figsize=(10,6))
plt.plot(range(1,40),acc,color = 'blue',linestyle='dashed',
marker='o',markerfacecolor='red', markersize=10)
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plt.title('accuracy vs. K Value')
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plt.xlabel('K')
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plt.ylabel('Accuracy')
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print("Maximum accuracy:‐",max(acc),"at K =",acc.index(max(acc)))
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