Data Science

Logistic Regression is a statistical model that models the probability of one event taking place by having the log-odds (the logarithm of the odds) fo

Linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as

Decision tree is a decision support tool that uses a tree-like model of decisions and their possible consequences, including chance event outcomes, re

Random forests is an ensemble learning method for classification, regression and other tasks that operates by constructing a multitude of decision tre

XGBoost, which stands for Extreme Gradient Boosting, is a scalable, distributed gradient-boosted decision tree (GBDT) machine learning library. It pro

LightGBM is a gradient boosting framework that uses tree based learning algorithms.간단히, 기존 GBM들보다 훨씬 더 빠르게 학습이 되는 모델이다이미지 출처 : https://lightgbm.r

k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in whi

Hierarchical Agglomerative Clustering (HCA) is a method of cluster analysis which seeks to build a hierarchy of clusters. Because this is 'Agglomerati

Spectral clustering techniques make use of the spectrum (eigenvalues) of the similarity matrix of the data to perform dimensionality reduction before

Credit card fraud detection 커널을 진행하다가, 해당 커널에 테스트 데이터셋이 분리되어 있지 않아 셀프로 데이터셋을 분리하며 알게된 정보를 공유하고자 한다머신러닝 모델에 Train 데이터를 전부 학습시킨 후 Test 데이터에 모델을 적용했을 때 성

이상거래 탐지 관련 머신러닝을 공부하다가(Kaggle : Credit card fraud detection), 성능 지표에 대한 개념을 맞닥뜨려 본 게시물을 작성하게 되었다. 오늘 포스팅 하는 Classification Evaluation Metrics(분류 성능 지표