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Commit 7f4c8b7a authored by Dean Samuel Schmitz's avatar Dean Samuel Schmitz
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Update documentation

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src/methods/nmf/nmf.cpp
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src/methods/nmf/nmf.pl
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:- module(nmf, [nmf/13]).
%% requirements of library(struct)
......@@ -15,9 +16,9 @@
%% definitions for the connected function
%% TODO:
%% --Input--
%% bool updateRuel => (1)true / (0)false,
%% string updateRule => ,
%% int maxIterations => 10000,
%% float32 minResidue => 1e-05,
%% mat data,
......@@ -28,6 +29,8 @@
%% mat H
%%
%% --Description--
%% Initilizes the nmf model and applies it to the given data.
%%
foreign(nmf, c, nmf(+string, +integer, +float32,
+pointer(float_array), +integer, +integer,
+integer,
......
src/methods/pca/pca.pl
+ 13
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:- module(pca, [pca/13,
pcaDimReduction/10,
pcaVarianceDimReduction/10]).
......@@ -17,7 +18,7 @@
%% definitions for the connected function
%% TODO:
%% --Input--
%% bool scaleData => (1)true / (0)false,
%% string decompositionPolicy "exact", "randomized", "randomized-block-krylov", "quic",
......@@ -29,13 +30,15 @@
%% mat eigVectors
%%
%% --Description--
%% Apply Principal Component Analysis to the provided data set.
%%
foreign(pca, c, pca( +integer, +string,
+pointer(float_array), +integer, +integer,
-pointer(float_array), -integer, -integer,
-pointer(float_array), -integer,
-pointer(float_array), -integer, -integer)).
%% TODO:
%% --Input--
%% bool scaleData => (1)true / (0)false,
%% string decompositionPolicy "exact", "randomized", "randomized-block-krylov", "quic",
......@@ -47,13 +50,16 @@ foreign(pca, c, pca( +integer, +string,
%% float32 Amount of Variance retained => [0,1]
%%
%% --Description--
%% Use PCA for dimensionality reduction on the given dataset.
%% Define the new dimensionality of the data with newDimension.
%%
foreign(pcaDimReduction, c, pcaDimReduction( +integer, +string,
+pointer(float_array), +integer, +integer,
+integer,
-pointer(float_array), -integer, -integer,
[-float32])).
%% TODO:
%% --Input--
%% bool scaleData => (1)true / (0)false,
%% string decompositionPolicy "exact", "randomized", "randomized-block-krylov", "quic",
......@@ -65,6 +71,9 @@ foreign(pcaDimReduction, c, pcaDimReduction( +integer, +string,
%% float32 Amount of Variance retained => [0,1]
%%
%% --Description--
%% Use PCA for dimensionality reduction on the given dataset.
%% Define to which variance the data should be reduced to.
%%
foreign(pcaVarianceDimReduction, c, pcaVarianceDimReduction( +integer, +string,
+pointer(float_array), +integer, +integer,
+float32,
......
src/methods/perceptron/perceptron.pl
+ 28
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:- module(perceptron, [ initModelNoTrain/3,
initModelWithTrain/7,
biases/2,
......@@ -20,6 +21,7 @@
%% definitions for the connected function
%% --Input--
%% int numClasses => 0,
%% int dimensionality => 0,
......@@ -27,8 +29,11 @@
%%
%% --Output--:
%% --Description--
%% Initilizes the perceptron model and its weight matrix but doesnt train it.
%%
foreign(initModelNoTrain, c, initModelNoTrain(+integer, +integer, +integer)).
%% --Input--
%% mat data => data(float_array), dataSize, dataRowNum,
%% vec labels => labels(float_array), labelsSize,
......@@ -37,7 +42,12 @@ foreign(initModelNoTrain, c, initModelNoTrain(+integer, +integer, +integer)).
%%
%% --Output--
%% --Description--
foreign(initModelWithTrain, c, initModelWithTrain(+pointer(float_array), +integer, +integer, +pointer(float_array), +integer, +integer, +integer)).
%% Initilizes the perceptron model and its weight matrix and trains it with the given data.
%%
foreign(initModelWithTrain, c, initModelWithTrain( +pointer(float_array), +integer, +integer,
+pointer(float_array), +integer,
+integer, +integer)).
%% --Input--
%%
......@@ -45,6 +55,8 @@ foreign(initModelWithTrain, c, initModelWithTrain(+pointer(float_array), +intege
%% vec biases => biases(float_array), biasesSize
%%
%% --Description--
%% Get the biases.
%%
foreign(biases, c, biases(-pointer(float_array), -integer)).
%% --Input--
......@@ -54,9 +66,12 @@ foreign(biases, c, biases(-pointer(float_array), -integer)).
%% vec predicLabels => predicLabels(float_array), predicLabelsSize
%%
%% --Description--
foreign(classify, c, classify(+pointer(float_array), +integer, +integer, -pointer(float_array), -integer)).
%% After training, use the weights matrix to classify test, and put the predicted classes in predictedLabels.
%%
foreign(classify, c, classify( +pointer(float_array), +integer, +integer,
-pointer(float_array), -integer)).
%% TODO:
%% --Input--
%% mat data => data(float_array), dataSize, dataRowNum,
%% vec labels => labels(float_array), labelsSize,
......@@ -65,7 +80,13 @@ foreign(classify, c, classify(+pointer(float_array), +integer, +integer, -pointe
%%
%% --Output--
%% --Description--
foreign(train, c, train(+pointer(float_array), +integer, +integer, +pointer(float_array), +integer, +integer, +pointer(float_array), +integer)).
%% Train the perceptron on the given data for up to the maximum number of iterations. This training does not reset the model weights, so you can call train/8 on multiple datasets sequentially.
%%
foreign(train, c, train(+pointer(float_array), +integer, +integer,
+pointer(float_array), +integer,
+integer,
+pointer(float_array), +integer)).
%% --Input--
%%
......@@ -73,6 +94,8 @@ foreign(train, c, train(+pointer(float_array), +integer, +integer, +pointer(floa
%% mat weights => weights(float_array), weightsColNum, weightsRowNum,
%%
%% --Description--
%% Get the weight matrix.
%%
foreign(weights, c, weights(-pointer(float_array), -integer, -integer)).
......
src/methods/radical/radical.pl
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:- module(radical, [ initModel/5,
doRadical/9,
doRadical2D/4]).
......@@ -17,7 +18,7 @@
%% definitions for the connected function
%% TODO:
%% --Input--
%% float32 noiseStdDev => 0.175,
%% int replicates => 30,
......@@ -28,9 +29,11 @@
%% --Output--
%%
%% --Description--
%% Initilizes the radical model.
%%
foreign(initModel, c, initModel(+float32, +integer, +integer, +integer, +integer)).
%% TODO:
%% --Input--
%% mat X
%%
......@@ -39,9 +42,13 @@ foreign(initModel, c, initModel(+float32, +integer, +integer, +integer, +integer
%% mat W
%%
%% --Description--
foreign(doRadical, c, doRadical(+pointer(float_array), +integer, +integer, -pointer(float_array), -integer, -integer, -pointer(float_array), -integer, -integer)).
%% Run RADICAL.
%%
foreign(doRadical, c, doRadical(+pointer(float_array), +integer, +integer,
-pointer(float_array), -integer, -integer,
-pointer(float_array), -integer, -integer)).
%% TODO:
%% --Input--
%% mat X
%%
......@@ -49,7 +56,10 @@ foreign(doRadical, c, doRadical(+pointer(float_array), +integer, +integer, -poin
%% float32 result of 2D radical
%%
%% --Description--
foreign(doRadical2D, c, doRadical2D(+pointer(float_array), +integer, +integer, [-float32])).
%% Two-dimensional version of RADICAL.
%%
foreign(doRadical2D, c, doRadical2D( +pointer(float_array), +integer, +integer,
[-float32])).
%% Defines the functions that get connected from main.cpp
......
src/methods/random_forest/random_forest.pl
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src/methods/sparse_coding/sparse_coding.pl
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