I'm attempting to create a Python 3 program to classify sentences into categories using Tensorflow. However, I'm getting a very lengthy series of errors when I try to run my code. The following error appears to be the foundation of my issue:
I am using Scikit-Learn's
LabelEncoder() method to create label IDs, which should meet this requirement; their documentation page says, "Encode labels with value between
The code I am trying to run is:
import tensorflow as tf import pandas as pd from sklearn import preprocessing from sklearn.model_selection import train_test_split data_df = pd.read_csv('data.csv') #data.csv has 2 columns: "Category", and "Description" features = data_df.drop('Category', axis=1) #drop Category column lab_enc = preprocessing.LabelEncoder() labels = lab_enc.fit_transform(data_df['Category']) #Encode labels with value between 0 and n_classes-1 labels = pd.Series(labels) #pandas_input_func needs the labels in Series format features_train, features_test, labels_train, labels_test = train_test_split(features, labels, test_size=0.3, random_state=101) description = tf.feature_column.categorical_column_with_hash_bucket('Description', hash_bucket_size=1000) feat_cols = [description] input_func = tf.estimator.inputs.pandas_input_fn(x=features_train, y=labels_train, batch_size=100, num_epochs=None, shuffle=True) model = tf.estimator.LinearClassifier(feature_columns=feat_cols) model.train(input_fn=input_func, steps=1000)
I'm at a bit of a loss as to how to proceed. I've only found one post referencing a similar issue here, but that user's issue appeared to be of a different nature to mine, if I'm understanding correctly.
Any insights are greatly appreciated!