91av视频/亚洲h视频/操亚洲美女/外国一级黄色毛片 - 国产三级三级三级三级

  • 大小: 6KB
    文件類型: .rar
    金幣: 2
    下載: 1 次
    發(fā)布日期: 2021-05-14
  • 語言: Matlab
  • 標簽: 機器學習??

資源簡介

源碼源自mathworks文件交換中心,優(yōu)于SMOTE的非平衡學習算法。(有意免金幣,但無法設置)

資源截圖

代碼片段和文件信息

function?[out_featuresSyn?out_labelsSyn]?=?ADASYN(in_features?in_labels?in_beta?in_kDensity?in_kSMOTE?in_featuresAreNormalized)
%this?function?implements?the?ADASYN?method?as?proposed?in?the?following
%paper:
%
%[1]:?H.?He?Y.?Bai?E.A.?Garcia?and?S.?Li?“ADASYN:?Adaptive?Synthetic
%Sampling?Approach?for?Imbalanced?Learning“?Proc.?Int‘l.?J.?Conf.?Neural
%Networks?pp.?1322--1328?(2008).
%
%the?implementation?follows?the?notation?and?equation?numbers?given?in
%section?3.1.4?of?another?paper:
%
%[2]:?H.?He?and?E.A.?Garcia?“Learning?from?imbalanced?data“
%Knowledge?and?Data?Engineering?IEEE?Transactions?on?21?no.?9
%pp.?1263--1284?(2009).
%
%
%the?purpose?of?the?ADASYN?method?is?to?improve?class?balance?towards
%equally-sized?classes?for?a?given?input?dataset.?this?is?achieved?by
%synthetically?creating?new?examples?from?the?minority?class?via?linear
%interpolation?between?existing?minority?class?samples.?this?approach?is
%known?as?the?SMOTE?method?cf.?section?3.1.3?in?[2].?ADASYN?is?an
%extension?of?SMOTE?creating?more?examples?in?the?vicinity?of?the?boundary
%between?the?two?classes?than?in?the?interior?of?the?minority?class.
%cf.?the?supplied?script?demo_ADASYN?for?an?example?of?this.
%
%
%?INPUTS:
%----------
%in_features:
%(N?\times?P)?matrix?of?numerical?features.?each?row?is?one?example?each
%column?is?one?feature?hence?there?are?N?examples?with?P?features?each.
%
%in_labels:
%boolean?N-vector?of?labels?defining?the?classes?to?which?the?examples?in
%in_features?belong.
%
%in_beta?[default:?1]:
%desired?level?of?balance?where?0?means?that?the?size?of?the?minority
%class?will?not?be?changed?and?1?means?that?the?minority?class?will?be
%ADASYNed?to?have?(approximately?due?to?rounding)?the?same?size?as?the
%majority?class.?any?value?of?in_beta?between?0?and?1?provides?a?compromise
%between?these?two?extremes.
%note?that?in_beta?IS?NOT?the?resulting?class?ratio?but?a?percentage?of
%how?much?class?balance?is?improved?in?comparison?to?the?given?class
%balance!?0?means?nothing?is?improved?in?comparison?to?the?given?class
%balance?and?1?means?class?sizes?are?perfectly?equalized?(except?for?small
%rounding-related?deviations).
%
%in_kDensity?[default:?5]:
%k?for?kNN?used?in?ADASYN?density?estimation?i.e.?in?calculation?of?the
%\Gamma_i?values?in?eq.?(4)?of?reference?[2].?this?is?the?kNN?call?that
%regards?examples?from?both?classes.
%
%in_kSMOTE?[default:?5]:?
%k?for?kNN?used?in?subsequent?SMOTE-style?synthesis?of?new?examples.
%this?is?the?kNN?call?that?regards?only?examples?from?the?minority?class.
%cf.?eq.?(1)?in?reference?[2].
%
%in_featuresAreNormalized?[default:?true]:
%boolean?indicating?whether?the?features?(i.e.?the?different?columns)?in
%in_features?are?already?normalized?to?the?same?scale?or?not.
%by?default?normalized?features?are?assumed?as?the?input?i.e.?the?user?is
%expected?to?apply?a?normalization?method?of?choice?before?passing?the?data
%to?the?AD

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----

?????文件??????12334??2019-02-20?15:17??ADASYN\ADASYN.m

?????文件???????3782??2019-02-20?15:24??ADASYN\demo_ADASYN.m

?????目錄??????????0??2019-02-20?15:25??ADASYN

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????????????????16116????????????????????3


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