Linear and Logistic Regression
- input format: LibSVM
- Local Example: run-linear.sh
- Runnig on Hadoop: run-hadoop.sh
- Set input data to stdin, and model_out=stdout
Parameters
All the parameters can be set by param=value
Important Parameters
- objective [default = logistic]
- can be linear or logistic
- base_score [default = 0.5]
- global bias, recommended set to mean value of label
- reg_L1 [default = 0]
- l1 regularization co-efficient
- reg_L2 [default = 1]
- l2 regularization co-efficient
- lbfgs_stop_tol [default = 1e-5]
- relative tolerance level of loss reduction with respect to initial loss
- max_lbfgs_iter [default = 500]
- maximum number of lbfgs iterations
Optimization Related parameters
- min_lbfgs_iter [default = 5]
- minimum number of lbfgs iterations
- max_linesearch_iter [default = 100]
- maximum number of iterations in linesearch
- linesearch_c1 [default = 1e-4]
- c1 co-efficient in backoff linesearch
- linesarch_backoff [default = 0.5]
- backoff ratio in linesearch