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LDA.py
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LDA.py
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from sklearn import datasets
import matplotlib.pyplot as plt
import numpy as np
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.preprocessing import StandardScaler
iris = datasets.load_iris()
X = iris.data
y = iris.target
sc = StandardScaler()
def twodim(d):
lda = LinearDiscriminantAnalysis(n_components=2)
d = sc.fit_transform(d)
lda_object = lda.fit(d, y)
d = lda_object.transform(d)
return d
def onedim(d):
lda = LinearDiscriminantAnalysis(n_components=1)
d = sc.fit_transform(d)
lda_object = lda.fit(d, y)
d = lda_object.transform(d)
return d
def plottwodim():
for l,c,m in zip(np.unique(y),['r','g','b'],['s','x','o']):
plt.scatter(twodim(X)[y==l,0],twodim(X)[y==l,1],c=c, marker=m, label=l,edgecolors='black')
plt.show()
def plotonedim():
for i in range(len(onedim(twodim(X)))):
if(y[i]==0):
plt.scatter(onedim(twodim(X))[i][0],0,marker='s',c='red',edgecolor='black')
elif (y[i]==1):
plt.scatter(onedim(twodim(X))[i][0],0,marker='x',c='green',edgecolor='black')
else :
plt.scatter(onedim(twodim(X))[i][0],0,marker='o',c='blue',edgecolor='black')
plt.show()
plottwodim()
plotonedim()
# lda2 = LinearDiscriminantAnalysis(n_components=1)
# lda_object2 = lda2.fit(X, y)
# X = lda_object2.transform(X)
# for i in range(len(X)):
# if(y[i]==0):
# plt.scatter(X[i][0],0,marker='s',c='red',edgecolor='black')
# elif (y[i]==1):
# plt.scatter(X[i][0],0,marker='x',c='green',edgecolor='black')
# else :
# plt.scatter(X[i][0],0,marker='o',c='blue',edgecolor='black')
# import numpy as np
# #from sklearn.lda import LDA
# from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
# X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
# y = np.array([1, 1, 1, 2, 2, 2])
# clf = LDA()
# clf.fit(X, y)
# LDA(n_components=None, priors=None, shrinkage=None, solver='svd',
# store_covariance=False, tol=0.0001)
# print(clf.predict([[-1, -1]]))
#print(X)
#print(y)
#print(X)
# i=0
# for l,c,m in zip(np.unique(y),['r','g','b'],['s','x','o']):
# plt2.scatter(X[i],0,c=c, marker=m, label=l,edgecolors='black')
# i =i+1
# print(X[i])