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https://issues.apache.org/jira/browse/MADLIB-1134?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Frank McQuillan updated MADLIB-1134:
------------------------------------
Description:
Follow on from https://issues.apache.org/jira/browse/MADLIB-413
Story
As a MADlib developer, I want to get 2nd phase implementation of NN going with
training and prediction functions, so that I can use this to build to an MVP
version for GA.
Features to add
* weights for inputs
* logic for n_tries
* multiple loss functions
* normalize inputs
* L2 regularization
was:
Multilayer perceptron with backpropagation
Modules:
* mlp_classification
* mlp_regression
Interface
{code}
source_table VARCHAR
output_table VARCHAR
independent_varname VARCHAR -- Column name for input features, should be a Real
Valued array
dependent_varname VARCHAR, -- Column name for target values, should be Real
Valued array of size 1 or greater
hidden_layer_sizes INTEGER[], -- Number of units per hidden layer (can be empty
or null, in which case, no hidden layers)
optimizer_params VARCHAR, -- Specified below
weights VARCHAR, -- Column name for weights. Weights the loss for each input
vector. Column should contain positive real value
activation_function VARCHAR, -- One of 'sigmoid' (default), 'tanh', 'relu', or
any prefix (eg. 't', 's')
grouping_cols
)
{code}
where
{code}
optimizer_params: -- eg "step_size=0.5, n_tries=5"
{
step_size DOUBLE PRECISION, -- Learning rate
n_iterations INTEGER, -- Number of iterations per try
n_tries INTEGER, -- Total number of training cycles, with random
initializations to avoid local minima.
tolerance DOUBLE PRECISION, -- Maximum distance between weights before training
stops (or until it reaches n_iterations)
}
{code}
> Neural Networks - MLP - Phase 2
> -------------------------------
>
> Key: MADLIB-1134
> URL: https://issues.apache.org/jira/browse/MADLIB-1134
> Project: Apache MADlib
> Issue Type: New Feature
> Components: Module: Neural Networks
> Reporter: Caleb Welton
> Assignee: Cooper Sloan
> Fix For: v1.12
>
>
> Follow on from https://issues.apache.org/jira/browse/MADLIB-413
> Story
> As a MADlib developer, I want to get 2nd phase implementation of NN going
> with training and prediction functions, so that I can use this to build to an
> MVP version for GA.
> Features to add
> * weights for inputs
> * logic for n_tries
> * multiple loss functions
> * normalize inputs
> * L2 regularization
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