lda

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
cols=['petal_len','petal_width','sepal_len','sepal_width','class']
df=pd.read_csv('iris.csv',header=None,names=cols)
df.head()
X=df.iloc[:,:4].values
y=df.iloc[:,4].values
#print(y)
#print(X)
from sklearn.preprocessing import StandardScaler, LabelEncoder
X=StandardScaler().fit_transform(X)
y=LabelEncoder().fit_transform(y)
from sklearn.model_selection import train_test_split
X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2)
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
lda=LinearDiscriminantAnalysis()
X_train=lda.fit_transform(X_train,y_train)
X_test=lda.transform(X_test)
plt.scatter(X_train[:,0],X_train[:,1],c=y_train);