- https://freshrimpsushi.github.io/ # 수학,수리통계 전반
- https://darkpgmr.tistory.com/103?category=460967 # 선형대수 관련
- http://wolfpack.hannam.ac.kr/ # 무친 무친 무친 무친
- https://scikit-learn.org/stable/auto_examples/linear_model/plot_ridge_path.html
- https://www.scikit-yb.org/en/latest/ # 오지네 진짜..
- https://www.analyticsvidhya.com/blog/2021/05/yellowbrick-visualization-for-model-predictions/
- https://cran.r-project.org/web/packages/jtools/vignettes/summ.html
- 평가지표들마다 약점들을 잘 파악할것
- MSE
- RMSE
- MAE
- R-squared
- 해결하고자하는 문제의 성격에 따라 bias variance tradeoff의 비율이 달라진다.
- Model complexity가 높아질 수록 과적합이 잘 일어난다.
- 일반화가 잘된 모델은 과적합이 덜된 모델
- https://datacookbook.kr/48
- https://modulabs-biomedical.github.io/Bias_vs_Variance
- https://bywords.tistory.com/entry/%EB%B2%88%EC%97%AD-%EC%9C%A0%EC%B9%98%EC%9B%90%EC%83%9D%EB%8F%84-%EC%9D%B4%ED%95%B4%ED%95%A0-%EC%88%98-%EC%9E%88%EB%8A%94-biasvariance-tradeoff
- https://rfriend.tistory.com/189
- 차수를 올릴수록 모델의 복잡도가 커진다.
- 모델의 복잡도가 올라가다가 어느 시점에서 과적합이 발생한다.
- https://stackoverflow.com/questions/20250771/remap-values-in-pandas-column-with-a-dict
- https://johnyejin.tistory.com/138
- https://www.mygreatlearning.com/blog/label-encoding-in-python/
- https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html
- http://www.leejungmin.org/post/2018/04/21/pandas_apply_and_map/
- https://stackoverflow.com/questions/7303322/apply-function-to-each-column-in-a-data-frame-observing-each-columns-existing-da
- https://stackoverflow.com/questions/43725799/map-multiple-columns-by-a-single-dictionary-in-pandas
- https://kanoki.org/2019/04/06/pandas-map-dictionary-values-with-dataframe-columns/
- https://m.blog.naver.com/yunjh7024/220880125898
- https://datalabbit.tistory.com/59
- https://m.blog.naver.com/yunjh7024/220880125898
- https://m.blog.naver.com/yunjh7024/220881024021
- .head()랑 .head 의 차이
- () 를 넣을 경우 default parameter가 들어간다.
- https://koreadatascientist.tistory.com/115
- http://www.leejungmin.org/post/2018/04/21/pandas_apply_and_map/
- https://stackoverflow.com/questions/20906474/import-multiple-csv-files-into-pandas-and-concatenate-into-one-dataframe
- https://stackoverflow.com/questions/18425225/getting-the-name-of-a-variable-as-a-string
- https://stackoverflow.com/questions/1538342/how-can-i-get-the-name-of-an-object-in-python
- https://stackoverflow.com/questions/1538342/how-can-i-get-the-name-of-an-object-in-python
- https://stackoverflow.com/questions/18425225/getting-the-name-of-a-variable-as-a-string
- https://stackoverflow.com/questions/38599015/print-object-instance-name-in-python/49331805
- https://www.geeksforgeeks.org/print-lists-in-python-4-different-ways/
- https://stackoverflow.com/questions/218616/how-to-get-method-parameter-names
- https://stackoverflow.com/questions/2217488/age-from-birthdate-in-python
- https://stackoverflow.com/questions/45704226/what-does-the-fit-method-in-scikit-learn-do
-
매우 매우 매우 중요
-
Classification
-
범주의 비율의 차이가 많이 날 경우 Accuracy를 쓰는 것이 부정확하다.
-
분류이긴 한데 결과가 확률로 나온다. -> 회귀모델처럶 해석가능하다.
-
기본적으로 GLM의 하위 관점에서 로지스틱 회귀를 바라보는 것이 중요하다.
-
특성이 1단위 증가할 때 마다 확률이 ~% 증가한다. 라고 해석한다
-
math
-
https://towardsai.net/p/machine-learning/logistic-regression-with-mathematics
-
https://medium.com/analytics-vidhya/logistic-regression-b35d2801a29c
- 구글에 '적률생성함수 정규분포' 검색할 것
- https://freshrimpsushi.github.io/posts/expectation-mean-variance-moment/
- http://blog.naver.com/PostView.nhn?blogId=mykepzzang&logNo=220846464280
- https://hsm-edu.tistory.com/1198
- https://hsm-edu.tistory.com/756
- https://freshrimpsushi.github.io/categories/%EC%88%98%EB%A6%AC%ED%86%B5%EA%B3%84%ED%95%99/
- ydataai/ydata-profiling#233 # pandas profiling안될때 : 삭제후 재설치
- https://rstudio-pubs-static.s3.amazonaws.com/41074_62aa52bdc9ff48a2ba3fb0f468e19118.html
- https://brunch.co.kr/@gimmesilver/38
- 중요
- 머신러닝 튜닝의 의미 : 하이퍼파라미터 탐색
- http://hleecaster.com/ml-training-validation-test-set/
- https://towardsdatascience.com/is-your-machine-learning-model-biased-94f9ee176b67
- https://youtu.be/4wGquWG-vGw
- https://machinelearningmastery.com/difference-test-validation-datasets/
- https://www.fast.ai/2017/11/13/validation-sets/ # 좋은 validation set을 만드는 방법
- 람다를 높일수록 스코어가 점점 낮아지고 상위 피처만 남는다
- 릿지회귀는 일종의 Feature Selection의 역할을 한다.
- 다항함수의 경우 람다를 높일 수록 스코어가 높아지고 어느 시점에서
- https://datascienceschool.net/03%20machine%20learning/06.05%20%EC%A0%95%EA%B7%9C%ED%99%94%20%EC%84%A0%ED%98%95%ED%9A%8C%EA%B7%80.html
- https://scikit-learn.org/stable/modules/linear_model.html # 공식문서 이론 매우매우 중요
- https://riverzayden.tistory.com/15 # 이론 중요
- https://blog.naver.com/wjddudwo209/220177096998
- https://student9725.tistory.com/31
- https://link.springer.com/referenceworkentry/10.1007%2F978-0-387-73003-5_1070
- https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeCV.html
- https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Ridge.html # Ridge cv와 ridge 구분
- https://frhyme.github.io/python-lib/pytlint/
- https://stackoverflow.com/questions/50358327/using-pylint-in-ipython-jupyter-notebook
- https://kiwidamien.github.io/encoding-categorical-variables.html
- https://www.kaggle.com/discdiver/category-encoders-examples
- https://contrib.scikit-learn.org/category_encoders/
- https://stats.idre.ucla.edu/r/library/r-library-contrast-coding-systems-for-categorical-variables/
- https://contrib.scikit-learn.org/category_encoders/onehot.html
- https://dkfl8151.tistory.com/12
- https://www.kaggle.com/subinium/11-categorical-encoders-and-benchmark
- 특성의 범주의 수를 카디널리티라고 한다.
- https://www.programcreek.com/python/example/93975/sklearn.feature_selection.f_regression
- https://machinelearningmastery.com/feature-selection-for-regression-data/
- https://scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectKBest.html
- 피처선택 후 이름가져오기
- https://www.emerald.com/insight/content/doi/10.1108/IJCS-10-2019-0029/full/html
- https://scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regression.html
- https://scikit-learn.org/stable/modules/permutation_importance.html#permutation-importance
- https://brunch.co.kr/@chris-song/34
- https://ko.wikipedia.org/wiki/%ED%8F%89%EA%B7%A0_%EC%A0%9C%EA%B3%B1%EA%B7%BC_%ED%8E%B8%EC%B0%A8
- https://partrita.github.io/posts/regression-error/
- http://matrix.skku.ac.kr/math4ai/part1/
- https://yngie-c.github.io/linear%20algebra/2020/09/12/projection/
- https://yngie-c.github.io/linear%20algebra/2020/02/19/LA3/
- https://yngie-c.github.io/linear%20algebra/2020/09/10/orthogonality/
- https://www.educative.io/courses/data-analysis-processing-with-pandas/q2pYRjnxlGR
- https://stackoverflow.com/questions/18551458/how-to-frame-two-for-loops-in-list-comprehension-python
- https://riptutorial.com/python/example/26610/iterate-two-or-more-list-simultaneously-within-list-comprehension
- https://excelsior-cjh.tistory.com/132
- https://stackoverflow.com/questions/1198777/double-iteration-in-list-comprehension
- https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html
- https://www.statisticshowto.com/probability-and-statistics/statistics-definitions/mean-squared-error/
- https://www.geeksforgeeks.org/python-mean-squared-error/
- Attribute and Parameter
####회귀
- https://wikidocs.net/21670 # 선형회귀 math 렉카필수
- http://norman3.github.io/prml/docs/chapter03/1
- https://datascienceschool.net/03%20machine%20learning/05.02%20%ED%9A%8C%EA%B7%80%EB%B6%84%EC%84%9D%EC%9D%98%20%EA%B8%B0%ED%95%98%ED%95%99.html
- https://stats.stackexchange.com/questions/123651/geometric-interpretation-of-multiple-correlation-coefficient-r-and-coefficient https://angeloyeo.github.io/2020/09/30/SVM.html # 초평면
- 선형회귀
- https://nicola-ml.tistory.com/23 #basics
- https://stackoverflow.com/questions/28669482/appending-pandas-dataframes-generated-in-a-for-loop # df for-loop 쌓기
- https://stackoverflow.com/questions/20461165/how-to-convert-index-of-a-pandas-dataframe-into-a-column # 시리스 데이터 DF로 변환,인덱스처리
- https://stackoverflow.com/questions/12235552/r-function-rep-in-python-replicates-elements-of-a-list-vector # python rep()사용
https://www.python-graph-gallery.com/
- https://matplotlib.org/stable/gallery/text_labels_and_annotations/annotation_demo.html
- https://stackoverflow.com/questions/39147492/annotate-seaborn-factorplot
- https://stackoverflow.com/questions/36780948/seaborn-matplotlib-how-to-repress-scientific-notation-in-factorplot-y-axis
- https://stackoverflow.com/questions/50744067/how-to-use-scientific-notation-in-pairplot-seaborn
- https://stackoverflow.com/questions/66485184/how-to-use-seaborn-scientific-notation-facetgrid-and-catplot
Perfomance Analitics 스타일 상관행렬 만들기
- https://stackoverflow.com/questions/48139899/correlation-matrix-plot-with-coefficients-on-one-side-scatterplots-on-another # 중요
- https://seaborn.pydata.org/generated/seaborn.pairplot.html
- https://datatofish.com/correlation-matrix-pandas/
- https://www.python-graph-gallery.com/scatter-plot/
- https://seaborn.pydata.org/generated/seaborn.scatterplot.html
- https://bryan7.tistory.com/826 # inspect를 활용한 메서드 소스 보기
- https://stackoverflow.com/questions/427453/how-can-i-get-the-source-code-of-a-python-function # 더많은 내용
- https://lasdri.tistory.com/809 # ssh git push 관련 에러
- https://parksb.github.io/article/28.html # 트러블슈팅
- 간단한 전처리
기하적 관점에서의 선형회귀
- https://stats.stackexchange.com/questions/123651/geometric-interpretation-of-multiple-correlation-coefficient-r-and-coefficient 선형회귀 모델들
- https://danbi-ncsoft.github.io/study/2018/05/04/study-regression_model_summary.html
- https://www.youtube.com/results?search_query=linear+algebra+regression
- https://m.blog.naver.com/PostView.naver?blogId=cto_hwangga&logNo=220616596327&proxyReferer=https:%2F%2Fwww.google.com%2F # 오차제곱합
- https://lovit.github.io/nlp/representation/2018/09/28/tsne/
- https://ratsgo.github.io/machine%20learning/2017/04/28/tSNE/
- https://yngie-c.github.io/machine%20learning/2020/10/10/tsne/
- https://www.youtube.com/watch?v=zpJwm7f7EXs
- https://www.slideshare.net/TaeohKim4/pr-103-tsne
- https://www.youtube.com/watch?v=NEaUSP4YerM&pp=ugMICgJrbxABGAE%3D
- https://darkpgmr.tistory.com/103 # 기초부터 활용
- https://cran.r-project.org/web/packages/matlib/vignettes/inv-ex1.html # inverse matrix in R
- https://ratsgo.github.io/linear%20algebra/2017/05/21/determinants/ # 행렬식
- https://angeloyeo. # github.io/2019/07/15/Matrix_as_Linear_Transformation.html # 행렬과 선형변환
- https://losskatsu.github.io/linear-algebra/linear-trans/#