Chapter 9 error in Sklearn "DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel(). y = column_or_1d(y, warn=True)"

[richlysakowski]

The code in Chapter 9 example on "Analyzing Wine Types"

wtp_dnn_predictions = le.inverse_transform(wtp_dnn_ypred)

throws a warning, and then a fatal error. I don't know how to fix this yet. Instructions are vague unclear.

C:\Programdata\Anaconda3\envs\tensorflow\lib\site-packages\sklearn\preprocessing_label.py:154: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
y = column_or_1d(y, warn=True)

---

ValueError Traceback (most recent call last)
Input In [40], in <cell line: 1>()
----> 1 wtp_dnn_predictions = le.inverse_transform(wtp_dnn_ypred)

File C:\Programdata\Anaconda3\envs\tensorflow\lib\site-packages\sklearn\preprocessing_label.py:161, in LabelEncoder.inverse_transform(self, y)
159 diff = np.setdiff1d(y, np.arange(len(self.classes_)))
160 if len(diff):
--> 161 raise ValueError("y contains previously unseen labels: %s" % str(diff))
162 y = np.asarray(y)
163 return self.classes_[y]

ValueError: y contains previously unseen labels: [0.12855081 0.12855084 0.1564262 ... 0.56348777 0.5781211 0.60708743]

[dipanjanS]

That's because you are creating the prediction labels in the wrong way. You can follow the process from here https://github.com/dipanjanS/adv_nlp_workshop_odsc_europe22/blob/main/02_NLP_Applications_Text_Classification_Deep_Learning_CNN_Models.ipynb and then pass the outputs to the label encoder.