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
MACHINE LEARNING MODELThe most important features and their gain values:
Matthews correlation coefficient (MCC) :
MACHINE LEARNING MODEL
ROC curve for classification resultsAUC=0.753
Matthews correlation coefficient for logistic regression for different values of probability threshold.
Matthews correlation coefficient for different samples sets
MACHINE LEARNING MODEL
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
MULTILEVEL MODEL
GENERALIZED LINEAR MODEL
Dependence of total within-clusters sum of squares from number of clusters.
Dependence of Lambda from AUC value.
Coefficients of the generalized linear model for logistic regression (Lambda=0.03 )
GENERALIZED LINEAR MODEL
GENERALIZED LINEAR MODEL
Histograms, correlation coefficients, pairs scatterplots for features.
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
BAYESIAN MODEL
Trace plot for Intercept parameter. Probability density function for Intercept parameter.
BAYESIAN MODEL
Box plots for logistic regression coefficients.
Combining Machine Learning withLinear and Bayesian Models
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):
Combining Machine Learning with Bayesian Model
Study of Reliability of PartsWeibull distribution
Thank you for your attention !
Special thanks to Bosch company for awarding me the travel grant for attending the IEEE BigData
2016 conference !