Posts
Developer notes and documentatoions.
Multidimensional Computer Adaptive Testing (MCAT): Procedure and Process
Multidimensional Computer Adaptive Testing (MCAT) extends the classical unidimensional CAT framework to simultaneously estimate multiple latent traits. This document details the theoretical foundations, algorithmic procedures, item selection strategies, ability estimation methods, and stopping rules that govern the MCAT process, with reference to seminal and contemporary literature.
The Actual Procedure and Process of Unidimension Computer Adaptive Testing (CAT)
omputerized Adaptive Testing (CAT) is a form of computer-based testing that adapts in real-time to each test-taker's ability level
Building a CAT Test with Guessing Parameter (3PL IRT) in Concerto Platform
Concerto Platform is open-source online adaptive testing platform.
Computer Adaptive Testing (CAT) Theory
Computer Adaptive Testing is a method of administering tests where **the difficulty of each question adapts in real-time based on the test-taker's ability**.
Text Classification for Survey Data Using SetFit
SetFit (Sentence Transformer Fine-Tuning) is a framework for few-shot text classification.
Decision Tree Classifier Concepts
Decision Tree atau pohon keputusan merupakan algoritma yang menggunakan graph berbentuk seperti pohon yang digunakan sebagai pendukung pengambilan keputusan.
LLMfy - Technical Features Overview
A comprehensive technical overview of LLMfy, a Python framework for building LLM-powered applications with multi-provider support, workflow orchestration, vector storage, and more.
Traditional RAG vs Agentic RAG
Machine learning is a subset of AI that involves developing algorithms that allow computers to learn from & make predictions or decisions based on data.