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An implementation of linear SVM for multiclass classification.
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```prolog
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:- use_module('path/to/.../src/methods/hoeffding_tree/hoeffding_tree.pl').
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%% usage example
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TrainData = [5.1,3.5,1.4, 4.9,3.0,1.4, 4.7,3.2,1.3, 4.6,3.1,1.5],
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TestData = [3,2,0, 5,1,4, 0,0,4, 3,3,5, 0,5,5, 2,5,5],
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hoeffding_tree_initAndBuildModel(gini_hoeffding, TrainData, 3, [0,1,0,1], 2, 0, 0.95, 5000, 100, 100, 10, 100),
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hoeffding_tree_classify(TestData, 3, PredicList, ProbsList).
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```
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# Available Predicates
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* [initModelWithTrain/10](/PrologMethods/Classification/linear_svm#initmodelwithtrain10)
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* [initModelNoTrain/4](/PrologMethods/Classification/linear_svm#initmodelnotrain4)
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* [classify/8](/PrologMethods/Classification/linear_svm#classify8)
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* [classifyPoint/3](/PrologMethods/Classification/linear_svm#classifypoint3)
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* [computeAccuracy/6](/PrologMethods/Classification/linear_svm#computeaccuracy6)
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* [train/8](/PrologMethods/Classification/linear_svm#train8)
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* [linear_SVM_initModelWithTrain/8](/PrologMethods/Classification/linear_svm#linear_svm_initmodelwithtrain8)
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* [linear_SVM_initModelNoTrain/4](/PrologMethods/Classification/linear_svm#linear_svm_initmodelnotrain4)
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* [linear_SVM_classify/5](/PrologMethods/Classification/linear_svm#linear_svm_classify5)
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* [linear_SVM_classifyPoint/2](/PrologMethods/Classification/linear_svm#linear_svm_classifypoint2)
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* [linear_SVM_computeAccuracy/4](/PrologMethods/Classification/linear_svm#linear_svm_computeaccuracy4)
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* [linear_SVM_train/6](/PrologMethods/Classification/linear_svm#linear_svm_train6)
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---
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| ... | ... | @@ -20,12 +30,22 @@ An implementation of linear SVM for multiclass classification. |
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Initializes the linear_svm model with the given data and trains it.
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```prolog
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%% part of the predicate definition
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initModelWithTrain( +pointer(float_array), +integer, +integer,
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%% predicate definition
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linear_SVM_initModelWithTrain(
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DataList, DataRows, LabelsList, NumClasses, Lambda, Delta, FitIntercept, Optimizer) :-
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NumClasses >= 0,
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Lambda >= 0.0,
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Delta >= 0.0,
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convert_list_to_float_array(DataList, DataRows, array(Xsize, Xrownum, X)),
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convert_list_to_float_array(LabelsList, array(Ysize, Y)),
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initModelWithTrainI(X, Xsize, Xrownum, Y, Ysize, NumClasses, Lambda, Delta, FitIntercept, Optimizer).
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%% foreign c++ predicate definition
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foreign(initModelWithTrain, c, initModelWithTrainI( +pointer(float_array), +integer, +integer,
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+pointer(float_array), +integer,
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+integer, +float32, +float32,
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+integer,
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+string).
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+string)).
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```
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### Parameters
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