GridSearchCV error "Too many indices in the array"

Question

I am using a supervised learning algorithm Random Forest classifier for training the data.

    clf = RandomForestClassifier(n_estimators=50, n_jobs=3, random_state=42)

Different parameter in the grid are:

    param_grid = { 
    'n_estimators': [200, 700],
    'max_features': ['auto', 'sqrt', 'log2'],
    'max_depth': [5,10],
    'min_samples_split': [5,10]
    }

Classifier "clf" and parameter grid "param_grid" are passed in the GridSearhCV method.

    clf_rfc = GridSearchCV(estimator=clf, param_grid=param_grid)

When I fit the features with labels using

    clf_rfc.fit(X_train, y_train)

I get the error "Too many indices in the array". Shape of X_train is (204,3) and of y_train is (204,1).

Tried with the option clf_rfc.fit(X_train.values, y_train.values) but could not get rid of the error.

Any suggestions would be appreciated !!

Also try reshaping your y_train to y_train.reshape(204) to make it a sequence from a 1-d array — Vivek Kumar
– Vivek Kumar, Commented Mar 21, 2017 at 14:33

Rafael Valero · Accepted Answer · 2018-03-13 10:16:07Z

5

As mentioned in previous post the problems appears to be in y_train which dimensions are (204,1). I think this is the problem instead of (204,1) should be (204,), click here for more info.

So if you rewrite y_train everything should be fine:

c, r = y_train.shape
y_train = y_train.reshape(c,)

If it gives as error such as: AttributeError: 'DataFrame' object has no attribute 'reshape' then try:

c, r = y_train.shape
y_train = y_train.values.reshape(c,)

edited Mar 13, 2018 at 10:16

answered Mar 12, 2018 at 17:36

Rafael Valero

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Comments

Rishikesh kumar · Accepted Answer · 2017-04-12 13:37:27Z

1

The shape of the 'y-train' dataframe is not correct. Try this:

clf_rfc.fit(X_train, y_train[0].values)

OR

clf_rfc.fit(X_train, y_train.values.ravel())

answered Apr 12, 2017 at 13:37

Rishikesh kumar

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Grimthorr · Accepted Answer · 2017-12-04 10:52:41Z

1

y_train should be a 1-dimensional array

I have tried clf_rfc.fit(X_train, y_train.flatten()), and it did work!

edited Dec 4, 2017 at 10:52

Grimthorr

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answered Dec 4, 2017 at 10:29

Simon J

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