real time ml with python

 # Train a logistic regression classifier to predict whether a flower is iris virginica or not

from sklearn import datasets
from sklearn.linear_model import LogisticRegression
import numpy as np
import matplotlib.pyplot as plt
iris = datasets.load_iris()
# print(list(iris.keys()))
# print(iris['data'].shape)
# print(iris['target'])
# print(iris['DESCR'])

X = iris["data"][:, 3:]
y = (iris["target"] == 2).astype(np.int)

# Train a logistic regression classifier
clf = LogisticRegression()
clf.fit(X,y)
example = clf.predict(([[2.6]]))
print(example)

# Using matplotlib to plot the visualization
X_new = np.linspace(0,3,1000).reshape(-1,1)
y_prob = clf.predict_proba(X_new)
print(y_prob)
plt.plot(X_new, y_prob[:,1], "g-", label="virginica")
plt.show()


# print(y)
# print(iris["data"])
# print(X)




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