<jupyter_start><jupyter_text>Some information about the Algorithm<jupyter_code>from sklearn import datasets
from sklearn.cross_validation import train_test_split
from sklearn.metrics import accuracy_score
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis

# load Iris dataset from sklearn 
iris =datasets.load_iris()
features = iris.data
# print (features)
labels = iris.target
# print(labels)

# split the data to 60% training and 40% testing
x_train,x_test,y_train,y_test=train_test_split(features,labels,test_size=.4)
print('Training samples is : ',len(x_train))
print('Testing samples is : ', len((x_test)))

LDA = LinearDiscriminantAnalysis()
clf = LDA.fit(x_train,y_train)
predictions = LDA.predict(x_test)
print('Training ......')
print ('Accuracy is : ',accuracy_score(y_test,predictions))<jupyter_output>Training samples is :  90
Testing samples is :  60
Training ......
Accuracy is :  0.983333333333
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