ultimate 2.0.2

ultimate

# ultimate Another neural network implemention for python

## Installation pip install ultimate

## Why Ultimate? + Support feature importance + Support missing values + Support am2x/a2m2x activation functions + Support hardmse/hardmax loss functions

## How To Use? <pre> # let’s use a simple example to learn how to use from ultimate.mlp import MLP import numpy as np

# generate sample X = np.linspace(-np.pi, np.pi, num=5000).reshape(-1, 1) Y = np.sin(X) print(X.shape, Y.shape)

# train and predict mlp = MLP(layer_size=[X.shape[1], 8, 8, 8, 1], loss_type=”mse”) mlp.train(X, Y, epoch_train=100, epoch_decay=10, verbose=1) pred = mlp.predict(X)

# show the result import matplotlib.pyplot as plt plt.plot(X, pred) plt.show() </pre>

## Examples + [Feature Importance](https://www.kaggle.com/anycode/feature-importance-using-nn) + [Image Regression](https://www.kaggle.com/anycode/image-regression) + [Iris Classification](https://www.kaggle.com/anycode/iris-classification) + [MNIST Recognition](https://www.kaggle.com/anycode/mnist-recognition)