Comments (4)
check the file above in link and please help me solve this problem
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having the same problem actually, can't figure out why.
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I solved this problem already long ago. Actually the shape of y_labels (which is polarity_train in my PDF I provided) is not in the required shape. Either it should (1400,1) or just list of 1400 class labels. As it's in array, because I used polarity_train.shape, so it should be in two dimensional. Just reshape your class labels to (1400,1) or use list of class labels. Hope it will solve too many indices problem in this case
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I also meet with this problems. I can't solve it no matter how I change the shape of data I used. Please tell me how to solve it if you truly solved.
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Related Issues (20)
- Is this project still maintained? HOT 1
- add more argument pass through from plot_cumulative_gain to matplotlib
- Add numerical digit precision parameter HOT 1
- The True label displays abnormal HOT 2
- Add a Silhouette coefficient plot for `clusterer` module HOT 2
- Plot confusion matrix not from predictions but from actual confusion matrix HOT 1
- plot feature importances: how to get the feature names out of a pipeline?
- plot_pca_2d_projection, order of classes/labels is not preserved
- Adding class_names option to gain and lift plots
- Actively Developed? HOT 2
- add class prediction error plot
- Regarding the scikit-plot.metrics.plot_roc function HOT 1
- [BUG] Build status badge not rendering correctly in readme
- Bug: Failing to import Scikitplot fails due to ImportError HOT 4
- Adding a parameter to plot_confusion_matrix() to hide overlaid counts HOT 7
- MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated
- ValueError: Found input variables with inconsistent numbers of samples HOT 3
- add classes_to_plot option to plot_cumulative_gain HOT 3
- Is there a [problem in precision_recall_curve? HOT 1
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