April 2020
Intermediate to advanced
344 pages
8h 22m
Japanese
Content preview from Pythonではじめる教師なし学習 ―機械学習の可能性を広げるラベルなしデータの利用
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300
13
章 時系列クラスタリング
tscResults.iloc[i][tscResults.iloc[i]==minValue]=-1
medianValue = tscResults.iloc[i].median()
tscResults.iloc[i][tscResults.iloc[i]==medianValue]=0
# Show results
tscResultsDF = pd.DataFrame(data=np.zeros((3,3)), \
index=["firstPlace","secondPlace","thirdPlace"], \
columns=["kShape", "kMeans","hdbscan"])
tscResultsDF.loc["firstPlace",:] = tscResults[tscResults==1].count().values
tscResultsDF.loc["secondPlace",:] = tscResults[tscResults==0].count().values
tscResultsDF.loc["thirdPlace",:] = tscResults[tscResults==-1].count().values
tscResultsDF
k-Shape
法が最も
1
位だった回数が多く、
HDBSCAN
がそれに続く。
k
平均法は
2
位だった回数が最
も多い。つまり多くのデータセットに対して最良ではないが最悪でもなかったというこ ...
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