presentationmachine learning, linear and bayesian models for logistic regression in failure...
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Machine Learning, Linear and Bayesian Models for Logistic Regression in Failure Detection Problems
B. Pavlyshenko (Ph.D.)SoftServe, Inc., Ivan Franko National University of Lviv, Lviv,Ukraine
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MACHINE LEARNING MODELThe most important features and their gain values:
Matthews correlation coefficient (MCC) :
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MACHINE LEARNING MODEL
ROC curve for classification resultsAUC=0.753
Matthews correlation coefficient for logistic regression for different values of probability threshold.
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Matthews correlation coefficient for different samples sets
MACHINE LEARNING MODEL
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ROC curve and Matthews correlation coefficient for different sets of features
MACHINE LEARNING MODEL
Features set 1:AUC=0.75
Features set 2:AUC=0.91
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MULTILEVEL MODEL
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GENERALIZED LINEAR MODEL
Dependence of total within-clusters sum of squares from number of clusters.
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Dependence of Lambda from AUC value.
Coefficients of the generalized linear model for logistic regression (Lambda=0.03 )
GENERALIZED LINEAR MODEL
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GENERALIZED LINEAR MODEL
Histograms, correlation coefficients, pairs scatterplots for features.
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BAYESIAN MODEL
model{ for (i in 1:n) { y[i] ~ dbern(p[i]) logit(p[i]) <- b0+inprod(b[ ],x[i,]) } b0 ~ dnorm(0,0.0001) for (j in 1:nfeat) { b[j] ~ dnorm(0,0.0001) }}
Probabilistic model for logistic regression using BUGS syntax
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BAYESIAN MODEL
Trace plot for Intercept parameter. Probability density function for Intercept parameter.
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BAYESIAN MODEL
Box plots for logistic regression coefficients.
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Combining Machine Learning withLinear and Bayesian Models
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Combining Machine Learning with Linear Model
Parameters set 1:max.depth = 15, colsample_bytree = 0.7
Parameters set 2:max.depth = 5, colsample_bytree = 0.7
Parameters set 3:max.depth = 15, colsample_bytree = 0.3
Matthews correlation coefficient for different XGBoost parameter sets (features set 2):
Matthews correlation coefficient for different XGBoost parameter sets (features set 1):
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Combining Machine Learning with Bayesian Model
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Study of Reliability of PartsWeibull distribution
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Thank you for your attention !
Special thanks to Bosch company for awarding me the travel grant for attending the IEEE BigData
2016 conference !