I’m trying to use the DL python network learner node for regression problem using tensorflow. I load the data as follows:
import tensorflow as tf
from TFModel import TFModel
import numpy as np
Get the training data from the table
x_train = input_table.iloc[0:77093, 1:63].values
y_train = input_table.iloc[0:77093, 0:1].values
#Get the validation data from the table
x_val = input_table.iloc[77094:, 1:63].values
y_val = input_table.iloc[77094:, 0:1].values
The above code loads x_train and y_train correctly. But I find that the x_val and y_val remains an empty array when executed. This leads to the validation loss over all epochs as 0. How can I resolve this ? I need to load the validation set and calculate the validation loss over epoch along with the training loss. Any suggestion is much appreciated.
I used this flow as reference to build mine: Train a MLP – KNIME Community Hub
Thanks in advance.