Digits Recongiation.py

#!/usr/bin/env python
# coding: utf-8

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import numpy as np
import pandas as pd
from sklearn.datasets import load_digits
get_ipython().run_line_magic('matplotlib', 'inline')
import matplotlib.pyplot as plt
digits = load_digits()


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plt.gray() 
for i in range(3):
    plt.matshow(digits.images[i])


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digits.target


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dir(digits)


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digits.target_names


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df = pd.DataFrame(digits.data,digits.target)
df


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df['target'] = digits.target
df.head(20)


# # Training and Testing model

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from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(df.drop('target',axis='columns'), df.target, test_size=0.5)


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from sklearn.svm import SVC
rbf_model= SVC(kernel='rbf')


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len(X_train)


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len(X_test)


# # Fitting the model

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rbf_model.fit(X_train, y_train)


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rbf_model.score(X_test,y_test)


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print('Accuracy =',rbf_model.score(X_test,y_test))


# # Using linear kernel

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linear_model= SVC(kernel='linear')
linear_model.fit(X_train,y_train)


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linear_model.score(X_test,y_test)


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print('Accuracy =',linear_model.score(X_test,y_test))


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from sklearn.externals import joblib


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