# MATLAB
Deep Learining using Neural Network Toolbox + Finance Portfolio Selection with MorningStar
## Artificial Nerual Network x 3 : Bodyfat Dataset
> * <a href="https://github.com/datarocksAmy/MATLAB/blob/master/Artificial%20Neural%20Network/NNminiProject1_a.m">ANN #1 - 10 Node + 1 Hidden Layer</a> </br>
> * <a href="https://github.com/datarocksAmy/MATLAB/blob/master/Artificial%20Neural%20Network/NNminiProject1_b.m">ANN #2 - 2 Nodes & 50 Nodes + 1 Hidden Later</a> </br>
> * <a href="https://github.com/datarocksAmy/MATLAB/blob/master/Artificial%20Neural%20Network/NNminiProject1_c.m">ANN #3 - Add regularization term</a> </br>
## Facial Recognition - AutoEncoder
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Facial%20Recognition/AutoEncoder%20OldSchool">AutoEncoder #1 - Traditional Approach</a> </br>
> * <a href="https://github.com/datarocksAmy/MATLAB/blob/master/Facial%20Recognition/AutoEncoder%20Part%20A/AutoEncoder_PartA.m">AutoEncoder #2 - Subject Specific : MSE Geuine and Imposter Scores </a> </br>
> * <a href="https://github.com/datarocksAmy/MATLAB/blob/master/Facial%20Recognition/AutoEncoder%20Part%20B/AutoEncoder_PartB.m">AutoEncoder #3 - Subject Independent</a> </br>
## Facial Recognition - PCA & LDA
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Facial%20Recognition-PCA/Mode%20One">PCA #1 : Mode #1</a></br>
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Facial%20Recognition-PCA/Mode%20Two">PCA #2 : Mode #2</a></br>
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Facial%20Recognition-LDA">LDA</a></br>
## Gesture Recognition - NARX Net
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Gesture%20Recognition-NARX/Pre-Fold">NARX #1 - Prefold</a> </br>
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Gesture%20Recognition-NARX/Subject%20Specific%20-%203CV">NARX #2 - Subject Specific : 3 Cross-Validatioon</a> </br>
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Gesture%20Recognition-NARX/Subject%20Independent%20-%206CV">NARX #3 - Subject Independent : 6 Cross-Validation</a> </br>
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Gesture%20Recognition-NARX/Committee/3CV">NARX #4 - Committee : 3 Cross-Validation</a> </br>
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Gesture%20Recognition-NARX/Committee/6CV">NARX #5 - Committee : 6 Cross-Validation</a> </br>
## Gesture Recognition - TDNN Net
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Gesture%20Recognition-TDNN/Prefold">TDNN #1 - Prefold</a> </br>
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Gesture%20Recognition-TDNN/Subject%20Specific-3CV">TDNN #2 - Subject Specific : 3 Cross-Validatioon</a> </br>
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Gesture%20Recognition-TDNN/Subject%20Independent-6CV">TDNN #3 - Subject Independent : 6 Cross-Validation</a> </br>
## Fingerprint Spoof Detector - Naive Bayes Classifier
> * <a href="https://github.com/datarocksAmy/MATLAB/blob/master/Fingerprint%20Spoof%20Detector-Naive%20Bayes/Bayes_Fingerprint_Spoof_Detector.m">Naive Bayes Classifier - Defalt Prior</a></br>
> * <a href="https://github.com/datarocksAmy/MATLAB/blob/master/Fingerprint%20Spoof%20Detector-Naive%20Bayes/Bayes_Fingerprint_Spoof_Detector_prior.m">Naive Bayes Classifier - Customized Prior</a></br>
## Radial Basis Function - Exact + Regular
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Radial%20Basis%20Function%20(Exact%20%26%20Regular)">RBF</a></br>
## Portfolio Selection with MorningStar
> * <a href="https://github.com/datarocksAmy/MATLAB/tree/master/Portfolio%20Selection%20Final%20Project)">Portfolio Selection 3-5 stars</a></br>
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Deep Learning using Neural Network Toolbox + Finance
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mat:2个
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Deep Learning using Neural Network Toolbox + Finance (152个子文件)
Final_Project_Portfolio_Selection.m 7KB
sixFoldCV.m 4KB
sixFoldCV.m 4KB
PCA_M2.m 3KB
slashConfusion.m 3KB
slashConfusion.m 3KB
MiniProject2_Task.m 3KB
inputHiddenOutputDelay.m 3KB
SubjectSpecific_3CV.m 3KB
SubjectSpecific_3CV.m 3KB
committee6CV.m 3KB
imgPrepModeTwo.m 3KB
threeFoldCV.m 3KB
imageCategory.m 3KB
imageCategory.m 3KB
imageCategory.m 3KB
imgPrepModeOne.m 3KB
imgPrepModeOne.m 3KB
PCA_imgPrep.m 3KB
LDA_imgPrep.m 2KB
imgPrep.m 2KB
imgPrep.m 2KB
imgPrep.m 2KB
threeFoldCV.m 2KB
committee3CV.m 2KB
PCA_Process.m 2KB
PCA_Process.m 2KB
AutoEncoder_PartA.m 2KB
GICalc_Instance_PCA.m 2KB
movementTarget.m 2KB
movementTarget.m 2KB
movementTarget.m 2KB
NNminiProject1_b.m 2KB
autoencoderModel.m 2KB
NNminiProject1_c.m 2KB
AutoEncoder_PartB.m 2KB
NNminiProject1_a.m 2KB
main3CV.m 2KB
depthsNodesDecision.m 2KB
MiniProject2.m 2KB
imageCategory.m 2KB
LDA_Model.m 2KB
autoEncoderModel.m 2KB
autoEncoderModel.m 2KB
LDAModel.m 2KB
LDAModel.m 2KB
confusionROCcommittee6CV.m 2KB
MultiInstance_Main.m 2KB
Bayes_Fingerprint_Spoof_Detector_prior.m 2KB
autoencoderModel.m 2KB
Bayes_Fingerprint_Spoof_Detector.m 2KB
MCS_Main.m 2KB
confusionROCSixF.m 2KB
PCA_Model.m 2KB
confusionROCSixF.m 2KB
PCA.m 2KB
PCA.m 2KB
LDA_for_PCA.m 2KB
SubjectIndependent_6CV.m 1KB
setupData.m 1KB
confusionROCcommittee.m 1KB
SubjectIndependent_6CV.m 1KB
GICalc_Instance_LDA.m 1KB
PCA_LDA_Combo.m 1KB
ModeTwo.m 1KB
Calc_Genuine_Impostor.m 1KB
Calc_Genuine_Impostor.m 1KB
Calc_Genuine_Impostor.m 1KB
GICalc_LDA.m 1KB
confusionROC.m 1KB
confusionROC.m 1KB
AutoEncoder_PartB.m 1KB
fiveTrainedInit.m 1KB
ModeOne.m 1KB
ModeOne.m 1KB
fiveTrainedInit.m 1KB
ImpostorCalc_PCA.m 1KB
ImpostorCalc.m 1KB
ImpostorCalc.m 1KB
ImpostorCalc.m 1KB
LDA_Main.m 1KB
shrinkConfusion.m 1018B
shrinkConfusion.m 1018B
shrinkConfusion.m 1018B
NNHW2.m 966B
main6CV.m 963B
parseData.m 941B
loadData.m 894B
trainImposterMSE.m 892B
testImposterMSE.m 846B
serializePersonXZ.m 809B
serializePersonXZ.m 809B
EncapsulatePerson.m 792B
EncapsulatePerson.m 792B
PCA_Instance_Main.m 792B
GenuineCalc_PCA.m 784B
GenuineCalc.m 775B
GenuineCalc.m 775B
roundData.m 756B
roundData.m 756B
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