ultimate 1.19.1

ultimate

# ultimate
A very simpe neural network implemention for python

## Installation
pip install ultimate

## Why Ultimate?
+ Super tiny and super easy
+ Support feature importance
+ Support missing values
+ Support am2/a2m2/am2l/a2m2l activation functions
+ Support hardmse/hardmax loss functions

## How To Use?
<pre>
from ultimate.mlp import MLP

mlp = MLP(
mi=0,
dtype='float64',
activation=[], # am2/a2m2/am2l/a2m2l
layer_size=[],
input_type='pointwise',
loss_type='mse', # mse/softmax/hardmse/hardmax
output_range=[0, 1],
output_shrink=0.001,
importance_mul=0.001,
leaky=-0.001,
dropout=0,
bias_rate=[0.005],
weight_rate=[],
regularization=1
)

mlp.train(
in_arr,
target_arr,
epoch_train=5,
epoch_decay=1,
iteration_log=100,
rate_init=0.06,
rate_decay=0.9,
importance_out=False,
loss_mul=0.001,
verbose=1,
shuffle=True
)

mlp.predict(
in_arr,
out_arr=None,
verbose=0,
iteration_log=100
)
</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/image-regression)
+ [MNIST Recognition](https://www.kaggle.com/anycode/mnist-recognition)