ValueError: bad input shape (60, 4) Iris dataset train_test_split

Question

I received an input shape error when using train_test_split for iris. I don't understand why. I have tested other datasets. train_test_split should handle this shape. Any suggestions? Thanks

    # Decision Tree Classifier
from sklearn import datasets
from sklearn import metrics
from sklearn.tree import DecisionTreeClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
# load the iris datasets
iris = datasets.load_iris()
#print(iris.data)
#print(dataset)
# fit a CART model to the data
model = LogisticRegression()
from sklearn.utils import shuffle
import numpy as np
#print(type(dataset.data))

#Xtrain = dataset.data[:int(0.8*len(dataset.data))]
#Ytrain = dataset.target[:int(0.8*len(dataset.data))]
#Xtest = dataset.data[int(0.8*len(dataset.data)):]
#Ytest = dataset.target[int(0.8*len(dataset.data)):]
Xtrain, Ytrain, Xtest, Ytest = train_test_split(iris.data.astype(np.float64), iris.target.astype(np.float64), test_size=0.4, train_size=0.6)
model.fit(Xtrain,Ytrain)
#print(model)
# make predictions
expected = Ytest
predicted = model.predict(Xtest)
# summarize the fit of the model
print(metrics.classification_report(expected, predicted))
print(metrics.confusion_matrix(expected, predicted))

Answer 1

Change the following line in your code, it should work!

Xtrain, Ytrain, Xtest, Ytest = train_test_split(iris.data.astype(np.float64), iris.target.astype(np.float64), test_size=0.4, train_size=0.6)

to:

Xtrain, Xtest, Ytrain, Ytest = train_test_split(iris.data.astype(np.float64), iris.target.astype(np.float64), test_size=0.4, train_size=0.6)

The order of the parameters you are accepting is not correct. See: http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html