Statistical Machine Learning (A)
0%
Previous
Course data
General
Announcements
Announcements
Announcements
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
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
Slide-3: Kernel
Kernel Density Estimator (KDE)
Nonparametric regression using Kernel estimator
Reproducing Kernel Hilbert Space (RKHS)
Week 4
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)
slide-5: Support Vector Regression (simulation) updated Sept-2021
Week 6 Model and Feature Selection/Engineering. Performance Evaluation.
VSURF - An R Package for Variable Selection Using Random Forests
slide-7: Model Selection, Feature Selection, and Performance Evaluation (update)
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 Decision tree-based approach
slide-6: Supervised learning: Decision Tree and Random Forest (updated)
Random Forest for Regresion
Week 7 Data with mixture type & extension of Kernel
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
Week 9 Introduction to NN
Introduction to NN
neural networks and statistical models
neural networks and statistical models (Powell & Duffy)
Week 10 linearity test
Material : linearity test
White test
TErasvirta test
Perceptron
And problem
Week 11
Multilayer perceptron
Gradient descent
backpropagation. xlxs
Week 12
Material MLP in Time Series
NN in SPSS
NN in R
Week 13
Quiz 21 Nov 2022
Week 14 - 15
The Performance of Ramsey Test, White Test and Terasvirta Test in Detecting Nonlinearity - A Simulation Study
plotXY.R
Simulation study on ESTAR model
Design of Experiment to Optimize the Architecture of Deep Learning for Nonlinear Time Series Forecasting
Pemilihan Arsitektur Terbaik pada Model Deep Learning
SVR for time series
nowcasting: predicting the present
Forecasting with RNN in Intermittent Demand Data
Week 16 EAS
Project SML S2
Next
Side panel
Panduan Dosen
Unduh PDF
[Video] Panduan Membuat Video Asinkronus dengan Power Point
Panduan Mahasiswa
Unduh PDF
Log in
Username
Password
Remember username
Forgot Password?
Log in
Log in using your account on
Don't have an account?
Statistical Machine Learning (A)
Home
Skip to main content
Course info
Home
Courses
Institut Teknologi Sepuluh Nopember
Magister
Fakultas Sains dan Analitika Data
S-2 STATISTIKA
Semester Gasal 2022/2023
Statistical Machine Learning (A)
Summary
Statistical Machine Learning (A)
Teacher:
Dedy Dwi Prastyo
Teacher:
Kartika Fithriasari