Lightweight library for neural network-based directional prediction
Project description
You need to install numpy
Activation finction
ReLU: relu(x) Relu derivative: relu_derivative(x) Sigmoid: sigmoid(x) Sigmoid derivative: sigmoid_derivative(x) Sigmoid derivative (without activation): sigmoid_derivative_from_output(s) Leaky ReLU: leaky_relu(x, alpha=0.01) Leaky ReLU derivative: leaky_relu_derivative(x, alpha=0.01) Soft max: softmax(z)
Loss
Cross entropy: cross_entropy(y_true, y_pred) MSE Loss: mse_loss(y_true, y_pred)
Metrics
Accuracy: accuracy(output, tags)
Utils
Stats: statistics(loss, error, output, epoch, accuracy)
There is feature in version 1.1. Thank for download
Made by: foloip Github: https://github.com/Foloip
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file DirNet-1.1.tar.gz.
File metadata
- Download URL: DirNet-1.1.tar.gz
- Upload date:
- Size: 3.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
22454face69aae5963c28230d059118f2785de25e84edb28189559e94f2dfdc7
|
|
| MD5 |
a9de506d191c64dfbc027d9598573678
|
|
| BLAKE2b-256 |
2b14fb79a95ea3d03631e0eb968ba8241808e83b4a7876000c17f19cde55b834
|
