Splunk® Machine Learning Toolkit

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Algorithm support of key ML-SPL commands quick reference

Use this quick reference to see which of the MLTK algorithms support the fit, apply, partial_fit, and summary commands. For additional details on each of these algorithms, see Algorithms in the Machine Learning Toolkit.

Anomaly Detection

Algorithm fit apply partial_fit summary
DensityFunction Y Y Y Y
LocalOutlierFactor Y N N N
OneClassSVM Y Y N N

Classifiers

Algorithm fit apply partial_fit summary
AutoPrediction Y Y N Y
BernoulliNB Y Y Y Y
DecisionTreeClassifier Y Y N Y
GaussianNB Y Y Y Y
GradientBoostingClassifier Y Y N Y
LogisticRegression Y Y N Y
MLPClassifier Y Y Y Y
RandomForestClassifier Y Y N Y
SGDClassifier Y Y Y Y
SVM Y Y N N

Clustering Algorithms

Algorithm fit apply partial_fit summary
Birch Y Y Y N
DBSCAN Y N N N
G-means Y Y N Y
K-means Y Y N Y
SpectralClustering Y N N N
X-means Y Y N Y

Cross-validation

Algorithm fit apply partial_fit summary
K-fold cross validation Y N N N

Feature Extraction

Algorithm fit apply partial_fit summary
FieldSelector Y Y N Y
HashingVectorizer Y N N N
ICA Y Y N N
KernelPCA Y Y N N
NPR Y Y N Y
PCA Y Y N Y
TFIDF Y Y N N

Preprocessing (Prepare Data)

Algorithm fit apply partial_fit summary
Imputer Y Y N Y
RobustScaler Y Y N Y
StandardScaler Y Y Y Y

Regressors

Algorithm fit apply partial_fit summary
AutoPrediction Y Y N Y
DecisionTreeRegressor Y Y N Y
ElasticNet Y Y N Y
GradientBoostingRegressor Y Y N Y
KernelRidge Y Y N N
Lasso Y Y N Y
LinearRegression Y Y N Y
RandomForestRegressor Y Y N Y
Ridge Y Y N Y
SGDRegressor Y Y Y Y
System Identification Y Y Y Y

Time Series Analysis

Algorithm fit apply partial_fit summary
ARIMA Y N N N
StateSpaceForecast Y Y Y Y

Utility Algorithms

Algorithm fit apply partial_fit summary
ACF Y N N N
PACF Y N N N
Last modified on 05 March, 2020
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This documentation applies to the following versions of Splunk® Machine Learning Toolkit: 5.2.0


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