@Override
public void cancel(Throwable ex) {
if (isCancelledOrCrashed()) return;
if (_model != null) _model.unlock(self());
if (ex instanceof JobCancelledException) {
if (!isCancelledOrCrashed()) cancel();
} else super.cancel(ex);
}
@Override
public void init() {
super.init();
if (lambda_search && lambda.length > 1)
throw new IllegalArgumentException(
"Can not supply both lambda_search and multiple lambdas. If lambda_search is on, GLM expects only one value of lambda, representing the lambda min (smallest lambda in the lambda search).");
// check the response
if (response.isEnum() && family != Family.binomial)
throw new IllegalArgumentException(
"Invalid response variable, trying to run regression with categorical response!");
switch (family) {
case poisson:
case tweedie:
if (response.min() < 0)
throw new IllegalArgumentException(
"Illegal response column for family='" + family + "', response must be >= 0.");
break;
case gamma:
if (response.min() <= 0)
throw new IllegalArgumentException(
"Invalid response for family='Gamma', response must be > 0!");
break;
case binomial:
if (response.min() < 0 || response.max() > 1)
throw new IllegalArgumentException(
"Illegal response column for family='Binomial', response must in <0,1> range!");
break;
default:
// pass
}
Frame fr =
DataInfo.prepareFrame(
source, response, ignored_cols, family == Family.binomial, true, true);
_dinfo = new DataInfo(fr, 1, use_all_factor_levels || lambda_search, standardize, false);
if (higher_accuracy) setHighAccuracy();
}
