Statistical Machine Learning (A)
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RANCANGAN PEMBELAJARAN SEMESTER
Week 1
Slide-1: Introduction to Predictive Analytics and Machine Learning
Slide-2: Data Analytics
credit-earning program of BDC competition: session 1 (Bagus Sartono) - Teknik Pembelajaran Mesin
credit-earning program of BDC competition: session 2 (Rangga Pratama) - Clustering in Business
credit-earning program of BDC competition: session 3 (Dedy Dwi Prastyo) - Unsupervised Machine Learning
credit-earning program of BDC competition: session 4 (Setia Pramana) - Bioscience Machine Learning
credit-earning program of BDC competition: session 5 (Sri Astuti Thamrin) - Supervised Learning (part 1)
credit-earning program of BDC competition: session 6 (Siti Mariyah) - Pemanfaatan Statistical Machine learning pada official statistics
credit-earning program of BDC competition: session 7a (R Bagus Fajriya Hakim) - Supervised Learning (part 2)
credit-earning program of BDC competition: session 7b (R Bagus Fajriya Hakim) - SVM
credit-earning program of BDC competition: session 7c (R Bagus Fajriya Hakim) - ANN
credit-earning program of BDC competition: session 8 (Yunanto Cahyo Putranto) - Business Intelligence
Week 2
SML (S2): Friday (Oct 9, 2020) at 13:00
Book: Yu-Wei, David Chiu - Machine Learning with R Cookbook_ Explore over 110 recipes to analyze data and build predictive models with the simple and easy-to-use R code-Packt Publishing (2015)
Article: Prescriptive analytics - Literature review and research challenges
Article: 50 Years of Data Science
Week 3
SML (S2): Friday (Oct 16, 2020) at 13:00
Slide-3: Kernel
Kernel Density Estimator (KDE)
Nonparametric regression using Kernel estimator
Reproducing Kernel Hilbert Space (RKHS)
Week 4
SML (S2): Friday (Oct 23, 2020) at 13:00
slide-3: Supervised Learning: Logistic Regression
slide-4: Supervised learning: SVM for Classification
illustration: SVM with polynomial kernel visualization
Week 5
slide-5: Support Vector Regression for Prediction
Support Vector Regression - a tutorial (1)
Support Vector Regression - a tutorial (2)
Week 6
SML (S2): Friday (Nov 6, 2020) at 13:00
slide-6: Supervised learning: Decision Tree and Random Forest (updated)
VSURF - An R Package for Variable Selection Using Random Forests
slide-7: Feature Selection dan Performance Evaluation
glmnet - Regularization Paths for Generalized Linear Models via Coordinate Descent
Statistical predictions with glmnet
penalizedSVM - a R-package for feature selection SVM classification
PlosONE The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets
Week 7 Data with mixture type & extension of Kernel
SML (S2): Friday (Nov 13, 2020) at 13:00
Tugas 1 (Batas akhir pengumpulan 15 November pukul 06:00 WIB)
kernlab – An S4 Package for Kernel Methods in R
SVM - The Interface to libsvm in package e1071
kernel PCA - Application of kernel PCA and computational machine learning to exploration of metabolites strongly associated with diet
mixKernel - Unsupervised multiple kernel learning for heterogeneous data integration
PCAmixdata R Package - Multivariate Analysis of Mixed Data
PCAmix - Outlier detection using PCA mix based T2 control chart
Project Analisis Deret Waktu dengan SML
Tugas SML untuk Analisis Deret Waktu
Project 2 Metode Klasifikasi
Project tentang Analisis dan Prediksi pada Metode Klasifikasi
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Statistical Machine Learning (A)
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Institut Teknologi Sepuluh Nopember
Magister
Fakultas Sains dan Analitika Data
S-2 STATISTIKA
Semester Gasal 2020/2021
Statistical Machine Learning (A)
Summary
Statistical Machine Learning (A)
Teacher:
Dedy Dwi Prastyo
Teacher:
Suhartono