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Update linear_svm authored by Dean Samuel Schmitz's avatar Dean Samuel Schmitz
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PrologMethods/Classification/linear_svm.md
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......@@ -25,14 +25,13 @@ hoeffding_tree_classify(TestData, 3, PredicList, ProbsList).
[links/resources](/PrologMethods/Classification/linear_svm#connected-linksresources)
## **_initModelWithTrain/10_**
## **_linear_SVM_initModelWithTrain/8_**
Initializes the linear_svm model with the given data and trains it.
```prolog
%% predicate definition
linear_SVM_initModelWithTrain(
DataList, DataRows, LabelsList, NumClasses, Lambda, Delta, FitIntercept, Optimizer) :-
linear_SVM_initModelWithTrain(DataList, DataRows, LabelsList, NumClasses, Lambda, Delta, FitIntercept, Optimizer) :-
NumClasses >= 0,
Lambda >= 0.0,
Delta >= 0.0,
......@@ -61,14 +60,21 @@ foreign(initModelWithTrain, c, initModelWithTrainI( +pointer(float_array), +inte
---
## **_initModelNoTrain/4_**
## **_linear_SVM_initModelNoTrain/4_**
Initializes the linear_svm model with the given data but doesnt train it.
```prolog
%% part of the predicate definition
initModelNoTrain( +integer, +float32, +float32,
+integer).
%% predicate definition
inear_SVM_initModelNoTrain(NumClasses, Lambda, Delta, FitIntercept) :-
NumClasses >= 0,
Lambda >= 0.0,
Delta >= 0.0,
initModelNoTrainI(NumClasses, Lambda, Delta, FitIntercept).
%% foreign c++ predicate definition
foreign(initModelNoTrain, c, initModelNoTrainI( +integer, +float32, +float32,
+integer)).
```
### Parameters
......@@ -81,15 +87,22 @@ initModelNoTrain( +integer, +float32, +float32,
---
## **_classify/8_**
## **_linear_SVM_classify/5_**
Classify the given points, returning class scores and predicted class label for each point.
```prolog
%% part of the predicate definition
classify( +pointer(float_array), +integer, +integer,
%% predicate definition
linear_SVM_classify(DataList, DataRows, LabelsList, ScoresList, ZCols) :-
convert_list_to_float_array(DataList, DataRows, array(Xsize, Xrows, X)),
classifyI(X, Xsize, Xrows, Y, Ysize, Z, ZCols, ZRows),
convert_float_array_to_list(Y, Ysize, LabelsList),
convert_float_array_to_2d_list(Z, ZCols, ZRows, ScoresList).
%% foreign c++ predicate definition
foreign(classify, c, classifyI( +pointer(float_array), +integer, +integer,
-pointer(float_array), -integer,
-pointer(float_array), -integer, -integer).
-pointer(float_array), -integer, -integer)).
```
### Parameters
......@@ -101,14 +114,19 @@ classify( +pointer(float_array), +integer, +integer,
---
## **_classifyPoint/3_**
## **_linear_SVM_classifyPoint/2_**
Classify the given point.
```prolog
%% part of the predicate definition
classifyPoint( +pointer(float_array), +integer,
[-integer]).
%% predicate definition
linear_SVM_classifyPoint(DataList, Prediction) :-
convert_list_to_float_array(DataList, array(Xsize, X)),
classifyPointI(X, Xsize, Prediction).
%% foreign c++ predicate definition
foreign(classifyPoint, c, classifyPointI( +pointer(float_array), +integer,
[-integer])).
```
### Parameters
......@@ -119,17 +137,23 @@ classifyPoint( +pointer(float_array), +integer,
---
## **_computeAccuracy/6_**
## **_linear_SVM_computeAccuracy/4_**
Computes accuracy of the learned model given the feature data and the labels associated with each data point.
Predictions are made using the provided data and are compared with the actual labels.
```prolog
%% part of the predicate definition
computeAccuracy( +pointer(float_array), +integer, +integer,
%% predicate definition
linear_SVM_computeAccuracy(DataList, DataRows, LabelsList, Accuracy) :-
convert_list_to_float_array(DataList, DataRows, array(Xsize, Xrownum, X)),
convert_list_to_float_array(LabelsList, array(Ysize, Y)),
computeAccuracyI(X, Xsize, Xrownum, Y, Ysize, Accuracy).
%% foreign c++ predicate definition
foreign(computeAccuracy, c, computeAccuracyI( +pointer(float_array), +integer, +integer,
+pointer(float_array), +integer,
[-float32]).
[-float32])).
```
### Parameters
......@@ -141,17 +165,24 @@ computeAccuracy( +pointer(float_array), +integer, +integer,
---
## **_train/8_**
## **_linear_SVM_train/6_**
Train the Linear_svm model with the given training data.
```prolog
%% part of the predicate definition
train( +pointer(float_array), +integer, +integer,
%% predicate definition
linear_SVM_train(DataList, DataRows, LabelsList, NumClasses, Optimizer, ObjValue) :-
NumClasses >= 0,
convert_list_to_float_array(DataList, DataRows, array(Xsize, Xrownum, X)),
convert_list_to_float_array(LabelsList, array(Ysize, Y)),
trainI(X, Xsize, Xrownum, Y, Ysize, NumClasses, Optimizer, ObjValue).
%% foreign c++ predicate definition
foreign(train, c, trainI( +pointer(float_array), +integer, +integer,
+pointer(float_array), +integer,
+integer,
+string,
[-float32]).
[-float32])).
```
### Parameters
......@@ -169,8 +200,8 @@ train( +pointer(float_array), +integer, +integer,
If you want a more detailed explanation, then go to the python documentation. There is most of the time a good explanation on how the methods work and what the parameters do.
* [**MLpack::linear_svm_C++\_documentation**](https://www.mlpack.org/doc/stable/doxygen/classmlpack_1_1svm_1_1LinearSVM.html)
* [**MLpack::linear_svm_Python_documentation**](https://www.mlpack.org/doc/stable/python_documentation.html#linear_svm)
* [**MLpack::linear_svm_C++\_documentation**](https://www.mlpack.org/doc/mlpack-3.4.2/doxygen/classmlpack_1_1svm_1_1LinearSVM.html)
* [**MLpack::linear_svm_Python_documentation**](https://www.mlpack.org/doc/mlpack-3.4.2/python_documentation.html#linear_svm)
added some of the links from the python documentation
......