I follow the code from this link 回帰:燃費を予測する | TensorFlow Core
error show in normalizer.adapt(np.array(train_features))
#train feature is my data
only this column has string value and cannot convert while i am using stackoverflow and etc.
I follow the code from this link 回帰:燃費を予測する | TensorFlow Core
error show in normalizer.adapt(np.array(train_features))
#train feature is my data
only this column has string value and cannot convert while i am using stackoverflow and etc.
tf.keras.layers.Normalization
performs feature wise normalization only on numerical features. You can use tf.keras.layers.StringLookup
which converts string categorical values an encoded representation that can be read by an Embedding
layer or Dense
layer. Thank you.
Thanks Chunduriv, I am very thankful for your answer but I solve this error last night. The issue is that some column are in other format string and int. So, first I can change into float64 all columns and then run, it was successfully solve.
And one more thing I forget that I changes all the data type float64 in dataframe but run the command in train_features so my friend check the code and tell me that you cannot change the data type in train_features, so I change the datatype in train_features and it was solved.