A wrapper provided for convenience around lnr_glm that sets
family = binomial(link = 'logit').
Arguments
- data
A dataframe to train a learner / learners on.
- formula
A regression formula to use inside this learner.
- weights
Observation weights; see
?lm- ...
Any extra arguments that should be passed to the internal model for model fitting purposes.
Value
A prediction function that accepts newdata, which returns
predictions for the probability of the outcome being 1/TRUE (a numeric
vector of values, one for each row of newdata).
Examples
lnr_logistic(mtcars, am ~ hp)(mtcars)
#> Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive
#> 0.4709653 0.4709653 0.5054301 0.4709653
#> Hornet Sportabout Valiant Duster 360 Merc 240D
#> 0.3443694 0.4810880 0.2293330 0.5679156
#> Merc 230 Merc 280 Merc 280C Merc 450SE
#> 0.5013718 0.4447781 0.4447781 0.3352648
#> Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental
#> 0.3352648 0.3352648 0.2916474 0.2751661
#> Chrysler Imperial Fiat 128 Honda Civic Toyota Corolla
#> 0.2515572 0.5599314 0.5877140 0.5619305
#> Toyota Corona Dodge Challenger AMC Javelin Camaro Z28
#> 0.4973132 0.3915135 0.3915135 0.2293330
#> Pontiac Firebird Fiat X1-9 Porsche 914-2 Lotus Europa
#> 0.3443694 0.5599314 0.5094877 0.4649025
#> Ford Pantera L Ferrari Dino Maserati Bora Volvo 142E
#> 0.2032172 0.3443694 0.1253601 0.4729882