Katalog Algoritma Machine Learning

Panduan lengkap algoritma Supervised, Unsupervised, dan Reinforcement Learning.

Supervised Learning

Regression (Prediksi Angka)

Linear Regression
Fondasi prediksi nilai kontinu.
KNN Regression
Prediksi berdasarkan tetangga terdekat.
Decision Tree Regression
Pohon keputusan untuk regresi.
Random Forest Regression
Ensemble banyak pohon.
Support Vector Regression (SVR)
Regresi dengan margin error.
Ridge Regression
Regularisasi L2.
Lasso Regression
Regularisasi L1 (Feature Selection).
Gradient Boosting Regressor
Ensemble bertahap.
Neural Network Regression
Deep Learning untuk regresi.

Classification (Kategorisasi)

Logistic Regression
Klasifikasi biner probabilitas.
KNN Classification
Klasifikasi tetangga terdekat.
Naive Bayes
Probabilitas Teorema Bayes.
Decision Tree Classifier
Pohon keputusan klasifikasi.
Random Forest Classifier
Hutan pohon keputusan.
SVM Classifier
Support Vector Machine.
Linear Discriminant Analysis (LDA)
Reduksi dimensi linier.
Gradient Boosting Classifier
Boosting bertahap.
MLP Classifier (Neural Network)
Jaringan syaraf tiruan.

Unsupervised Learning

Clustering (Pengelompokan)

K-Means Clustering
Pengelompokan berbasis Centroid.
Mean-Shift Clustering
Sliding window density.
DBSCAN
Density-based clustering.
Agglomerative Hierarchical
Pohon hierarki cluster.
Gaussian Mixture Models (GMM)
Probabilistic soft clustering.
Spectral Clustering
Graph-based clustering.
OPTICS Clustering
DBSCAN but better for varying density.
BIRCH Clustering
Optimized for Big Data.
Affinity Propagation
Examplar based, no K required.

Reinforcement Learning

Decision Making (Pengambilan Keputusan)

Q-Learning
Off-policy value iteration.
SARSA
On-policy value iteration.
Deep Q-Network (DQN)
Deep Reinforcement Learning.
Thompson Sampling
Multi-Armed Bandit (Probabilistic).
Upper Confidence Bound (UCB)
Multi-Armed Bandit (Deterministic).
R-Learning
Average Reward Learning.
TD Learning
Temporal Difference Prediction.