Prediction on Perceptron using Iris Dataset

[ambika.insa1994]

in the code below,help me with the predict line writtern,what does the numbers writtern in the predict means

import numpy as np
from sklearn.datasets import load_iris
from sklearn.linear_model import Perceptron
iris = load_iris()
X = iris.data[:, (2, 3)] # petal length, petal width
y = (iris.target == 0).astype(np.int) # Iris Setosa?
per_clf = Perceptron()
per_clf.fit(X, y)
y_pred = per_clf.predict([[2, 0.5]])

[sanjayk]

iris data set has 4 features by default

@ambika.insa1994

X = iris.data[:, (2, 3)] # petal length, petal width
y = (iris.target == 0).astype(np.int) # Iris Setosa?

But you are building your training data X only using two features ( (2, 3) -> features at index 2 and index 3)

@ambika.insa1994

per_clf.fit(X, y)
y_pred = per_clf.predict([[2, 0.5]])

Once your model per_clf is built using fit function, you are making prediction for a new instance. And the instance should have 2 features which you are passing as 2 and 0.5.