Tests a multinomial logistic regression model

This algorithm is a sequential one. The platform will call its process() method once per data incoming on its inputs.

Algorithms have at least one input and one output. All algorithm endpoints are organized in groups. Groups are used by the platform to indicate which inputs and outputs are synchronized together. The first group is automatically synchronized with the channel defined by the block in which the algorithm is deployed.

Group: main

Endpoint Name Data Format Nature
image system/array_2d_uint8/1 Input
label system/uint64/1 Output

Group: model

Endpoint Name Data Format Nature
model system/text/1 Input

The code for this algorithm in Python
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This algorithm contains a logistic regression model trained on the MNIST database. It takes as input images of digits and outputs the classification label of images.


Updated Name Databases/Protocols Analyzers
amohammadi/amohammadi/mnist_simple/1/mnist1 mnist/5@idiap amohammadi/accuracy_analyzer/1

This table shows the number of times this algorithm has been successfully run using the given environment. Note this does not provide sufficient information to evaluate if the algorithm will run when submitted to different conditions.

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