Updated SparseSVMFunction and added basic implementation of SparseSVM Class.
List of changes:
1) Moved the code for `sparse_svm_function.hpp` and `sparse_svm_function_impl.hpp`under the mlpack namespace.
2) Fixed missing dependency issue for `MakeAlias` and `ShuffleData` in `sparse_svm_function_impl.hpp`.
3) Added `EvaluateWithGradient()` for `SparseSVMFunction` class.
4) Added a basic starter code for `SparseSVM` class.
fixed syntax issues
fixed syntax issues
fixed syntax issues
fixed inconsistency in optimizer type
fixed some inconsistency
updated SparseSVM::Classify and added SparseSVM::ComputeAccuracy()
updated SparseSVM::Classify() and added SparseSVM::ComputeAccuracy().
List of changes.
- updated `SparseSVM::Classify()`.
- added `SparseSVM::ComputeAccuracy()`.
- removed `SparseSVM::FeatureSize()` since `parameters` is a concatenated vector of `w` and `b`.
- added `sparse_svm.hpp` and `sparse_svm.cpp` to `../sparse_svm/CMakeLists.txt`.
fixed SparseSVMFunction::Evaluate() and fixed an issue in SparseSVM::Classify() (#21)
* fixed SparseSVMFunction::Evaluate()
Updated the function definition for `SparseSVMFunction::Evaluate()` and `SparseSVMFunction::EvaluateWithGradient()` and used arma::clamp().
* fixed an issue in SparseSVM::Classify()
The issue was related to typecasting. The parameter inside `arma::size()` should have the same type as that of `labels`.
Updated SparseSVMFunction::Evaluate() and SparseSVMFunction::Gradient().
First Small Test for class SparseSVMFunction
Fixed Syntax issue and some other issue.
Added SparseSVMFunctionRandomEvaluate test.
test: SparseSVMFunctionGradient
added sparse_svm_impl.hpp
Templatized SparseSVM and SparseSVMFunction.
Updated implementation of SparseSVMFunction.
This takes into account the fact that labels is of type `arma::Row<size_t>` and converts it into appropriate type for the calculation of hinge loss.
Added L2-Regularization.
Added Documentation.
Updated implementation to adapt multiple class classification.
fixed syntax inconsistency
ayesdie