## page was renamed from 機械学習
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[[TableOfContents]]

= 概要 =
機械学習

= インストール =
http://conda.pydata.org/miniconda.html

= 関連ライブラリ =
 * ["NumPy"]
 * ["scikit-learn"]
 * ["word2vec"]
 * ["DeepLearning"]

= アルゴリズム等 =

== 辞書 ==
 * [http://hivecolor.com/id/65 tfidf、LSI、LDAの違いについて調べてみた - Hive Color]
 * [http://hivecolor.com/id/88 tfidf, lsi, ldaを使ったツイッターユーザーの類似度計算 - Hive Color]

== SVM ==
 * [http://qiita.com/pika_shi/items/5e59bcf69e85fdd9edb2 SVMを使いこなす！チェックポイント8つ]
 * [http://qiita.com/sz_dr/items/f3d6630137b184156a67 SVM(RBFカーネル)のハイパーパラメータを変えると何が起こるの?]

== 不均衡データ ==
 * [http://www.slideshare.net/sfchaos/ss-11307051 不均衡データのクラス分類]
 * [http://d.hatena.ne.jp/dichika/20130424/p1 Crowdsolvingに参加して7/42位だった]


 * SMOTE
 * Granular Support Vector Machines

== multiclass-multilabel ==
* [http://stackoverflow.com/questions/10526579/use-scikit-learn-to-classify-into-multiple-categories python - use scikit-learn to classify into multiple categories - Stack Overflow]

== Active Learning ==
 * [http://www.slideshare.net/shuyo/introduction-to-active-learning-25787487 Active Learning 入門]

= 表示 =
pd.crosstab

 * [http://stackoverflow.com/questions/5821125/how-to-plot-confusion-matrix-with-string-axis-rather-than-integer-in-python matplotlib - How to plot confusion matrix with string axis rather than integer in python - Stack Overflow]:confusion matrix のグラフを綺麗な画像にする

 * https://github.com/wellflat/cat-fancier/blob/master/classifier/bin/report.py
 * https://github.com/alxndrkalinin/mi-pred/blob/master/ML.py
 * http://akiniwa.hatenablog.jp/entry/2013/08/11/182756
 * http://qiita.com/wellflat/items/0b6b859bb275fd4526ed

= グラフ =
 * http://bokeh.pydata.org/en/latest/index.html
 * https://github.com/mwaskom/seaborn

 * [http://matplotlib.org/examples/color/colormaps_reference.html color example code: colormaps_reference.py — Matplotlib 1.4.2 documentation]

 * http://nbviewer.ipython.org/github/bugra/pydata-nyc-2014/blob/master/3.%20Scikit%20Learn%20-%20Supervised%20Learning.ipynb
 * http://bokeh.pydata.org/en/latest/docs/gallery/cat_heatmap_chart.html
 * http://isaacslavitt.com/2014/10/24/spdc-lightning-talk/

 * http://nbviewer.ipython.org/github/jakevdp/ESAC-stats-2014/blob/master/notebooks/05.2-Clustering-KMeans.ipynb

 * http://www.interaction-ipsj.org/archives/paper2013/data/Interaction2013/oral/data/pdf/13INT001.pdf

= AUC =
 * http://scikit-learn.org/stable/auto_examples/plot_roc.html
 * http://scikit-learn.org/stable/auto_examples/plot_roc_crossval.html
 * https://gist.github.com/coreylynch/4150976
 * http://www.hpl.hp.com/techreports/2003/HPL-2003-4.pdf
 * http://otndnld.oracle.co.jp/document/products/oracle10g/102/doc_cd/datamine.102/B19263-01/3predictive.htm

= R関連 =
 * [https://atnd.org/events/22039 R Advent Calendar 2011]
 * [https://atnd.org/events/31973 R Advent Calendar 2012]
 * [https://atnd.org/events/45043 R Advent Calendar 2013]
 * [https://atnd.org/events/58648 R Advent Calendar 2014]

= 用語メモ =
カッパ係数 kappa、自由回答，インタビューなどの分類の信頼性，一致度 http://www.mizumot.com/stats/kappa.htm

= 未分類 =
[http://www.shojiro-tanaka.net/gradOutputs/2004/saitoH.pdf 機械学習の評価]

[http://universityofbigdata.net/competition/tutorial/5681717746597888 テキスト分類問題その１ チュートリアル]

[https://github.com/notani/uob/tree/master/03_text uob/03_text at master · notani/uob · GitHub]

= 参考サイト =
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CategoryTechnical