Using multiple features with scikit-learn

Question

I'm working on text classification using scikit-learn. Things work well with a single feature, but introducing multiple features is giving me errors. I think the problem is that I'm not formatting the data in the way that the classifier expects. For example, this works fine: ``` data = np.array(df['feature1']) classes = label_encoder.transform(np.asarray(df['target'])) X_train, X_test, Y_train, Y_test = train_test_split(data, classes) classifier = Pipeline(...) classifier.fit(X_train, Y_train) ``` But this: ``` data = np.array(df[['feature1', 'feature2']]) classes = label_encoder.transform(np.asarray(df['target'])) X_train, X_test, Y_train, Y_test = train_test_split(data, classes) classifier = Pipeline(...) classifier.fit(X_train, Y_train) ``` dies with ``` Traceback (most recent call last): File "/Users/jed/Dropbox/LegalMetric/LegalMetricML/motion_classifier.py", line 157, in <module> classifier.fit(X_train, Y_train) File "/Library/Python/2.7/site-packages/sklearn/pipeline.py", line…

Accepted Answer

The particular error message makes it seem like your code somewhere expects something to be a `str` (so that `.lower` may be called) but instead it is receiving a whole array (probably a whole array of `str`s).

Can you edit the question to better describe the data and also post the full traceback, not just the small part with the named error?

In the meantime, you can also try

```
data = df[['feature1', 'feature2']].values
```

and

```
df['target'].values
```

instead of explicitly casting to `np.ndarray` yourself.

It looks to me like an array is being made where it is 1x1 and the singleton element in the "array" is itself an `ndarray`.

Using multiple features with scikit-learn

Solution

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