목록Reference (45)
Forward Selection and Backward Elimination
https://yngie-c.github.io/machine%20learning/2020/09/06/fs_be/ 전진 선택(Forward Selection)과 후진 제거(Backward Elimination) · Data Science 해당 게시물은 고려대학교 강필성 교수님의 강의를 바탕으로 작성한 것입니다. Wrapper 래퍼(Wrapper)는 특성 선택(Feature selection)에 속하는 방법 중 하나로, 반복되는 알고리즘을 사용하는 지도 학습 yngie-c.github.io https://online.stat.psu.edu/stat501/lesson/10/10.2
Exponential family of distributions and generalized linear model (GLM)
https://www.math.snu.ac.kr/~hichoi/machinelearning/lecturenotes/ExpFam_GLM.pdf
Hilbert space
https://jaejunyoo.blogspot.com/2020/03/signal-processing-for-communications-3-1.html?fbclid=IwAR2I1PlptZKQt--V0Ci-DYuCcKLcYkAhkqmp3SsSgUUMNvbl4FQIZAxIeDQ&m=1 Signal Processing For Communications (3-1) Machine learning and research topics explained in beginner graduate's terms. 초짜 대학원생의 쉽게 풀어 설명하는 머신러닝 jaejunyoo.blogspot.com
Likelihood ratio test - Normal for unknown variance
http://dlinares.org/lrtnormalunknownvariance.html Likelihood ratio test: normal for unknown variance \(\sigma^2\) is a nuisance parameter. Two-side composite hypothesis test \(X_1,\dotsc,X_n \sim N(\mu,\sigma^2)\) \(H_0: \mu = \mu_0\) \(H_1: \mu \neq \mu_0\) \[\Lambda \left( x \right) = \frac{ sup \{ L(\theta | x) : \theta \in \Theta_0 \}}{sup \{ L(\theta dlinares.org
Deterministic model vs Stochastic model
https://analyticsindiamag.com/deterministic-vs-stochastic-machine-learning/ Deterministic vs Stochastic Machine Learning A deterministic approach has a simple and comprehensible structure compared to a stochastic approach. analyticsindiamag.com
Time series analysis using techniques in R
https://rpubs.com/Deeandrea/276948 RPubs - Basic Time Series Analysis rpubs.com https://2stndard.tistory.com/126 시계열 이상치 탐색 in R 이상치 탐색 이상치는 시계열 데이터 상의 추세나 계절성에 반하여 나타나는 특별한 데이터를 말하는데 영어로는 outlier 혹은 anomaly라고 한다. 이 이상치는 측정상의 오류나 데이터 자체의 오류 2stndard.tistory.com https://rpubs.com/AlgoritmaAcademy/multiseasonality RPubs - Forecasting Time Series with Multiple Seasonal rpubs.com ts객체 만들때 frequency를..
Understanding outliers in time series analysis
https://pro.arcgis.com/en/pro-app/latest/tool-reference/space-time-pattern-mining/understanding-outliers-in-time-series-analysis.htm Understanding outliers in time series analysis—ArcGIS Pro | Documentation Understanding outliers in time series analysis Outliers in time series data are values that significantly differ from the patterns and trends of the other values in the time series. For examp..
