Configure Your Neural Network

Before diving into data classification, let’s set up your neural network. Our setup section is designed to guide you through the process of configuring the basic structure of your network. Adjust the layers, nodes, and more.
Important: changing any option in this section will reset the network weights.

Input Layer Height

Hidden Layers Count

Output Layer Height

Activation Function

Loss Function

Output Function

Normalization

It’s Super Fast, Give it a Try!

Now that your neural network is configured, let’s put it to the test. Upload your data, train the network, and then evaluate its performance.

Encoding Technique
Data is always encoded if categorical columns are detected.

Label Encoding (0, 1, 2,...)

One-Hot Encoding (001, 010, 100, ...)

Show original data in preview

Training Data

Testing Data

Train/Pause:

Speed does not affect training accuracy

Learning Rate (Safe to change, does not reset the weights)

Training Error Goal (Training auto stops once reached)

Testing Error Goal (Training auto stops once reached)

Options:

Include Testing Data

Training and Testing Errors:

Training Error: N/A

Testing Error: N/A

Options:

Decode Data (If Necessary)

Show Input Data

Custom Test

Inputs (Seperated by ',' characters)

Configure Your Neural Network

Structure Setup

Advanced Settings

It’s Super Fast, Give it a Try!

Data Preparation

Training Data

Testing Data

Training Your Module

Train/Pause:

Fixed Epochs:

Options:

Training and Testing Errors:

Testing & Evaluation

Options:

Custom Test