Fix failed tests

h2oai · Sep 21, 2023 · 821cb4e · 821cb4e
1 parent b490cfa
commit 821cb4e
Show file tree

Hide file tree

Showing 3 changed files with 10 additions and 10 deletions.
diff --git a/h2o-algos/src/main/java/hex/tree/uplift/UpliftDRFModel.java b/h2o-algos/src/main/java/hex/tree/uplift/UpliftDRFModel.java
@@ -88,7 +88,7 @@ public void initActualParamValues() {
     }
 
     @Override
-    public ModelMojoWriter getMojo() {
+    public UpliftDrfMojoWriter getMojo() {
         return new UpliftDrfMojoWriter(this);
     }
 

diff --git a/h2o-py/h2o/model/model_base.py b/h2o-py/h2o/model/model_base.py
@@ -480,16 +480,14 @@ def model_performance(self, test_data=None, train=False, valid=False, xval=False
 
             If type is ``"auto"`` or ``"none"``, AUC and AUCPR are not calculated.
         :param String auuc_type: Change default AUUC type for uplift binomial classification AUUC calculation 
-            when ``test_data`` is not None. One of:
-
-                - ``"AUTO"`` (default)
+            when ``test_data`` is not None. One of:    
+                - ``"AUTO"`` 
                 - ``"qini"``
                 - ``"lift"``
                 - ``"gain"``
+                - None (default)
                 
             If type is ``"auto"`` ("qini"), AUUC is calculated. 
-        :param int auuc_nbins: Number of bins for calculation AUUC. Defaults to ``-1``, which means 1000.
-        :param list float: List of custom thresholds to calculate AUUC when ``test_data`` is not None. Defaults None.
         :returns: An instance of :class:`~h2o.model.metrics_base.MetricsBase` or one of its subclass.
         """
 

diff --git a/h2o-r/h2o-package/R/models.R b/h2o-r/h2o-package/R/models.R
@@ -1021,6 +1021,7 @@ h2o.feature_frequencies <- feature_frequencies.H2OModel
 #' @param data (DEPRECATED) An H2OFrame. This argument is now called `newdata`.
 #' @param auc_type For multinomila model only. Set default multinomial AUC type. Must be one of: "AUTO", "NONE", "MACRO_OVR", "WEIGHTED_OVR", "MACRO_OVO",
 #'        "WEIGHTED_OVO". Default is "NONE"
+#' @param auuc_type For binomial model only. Set default AUUC type. Must be one of: "AUTO", "GINI", "GAIN", "LIFT". Default is NULL. 
 #' @return Returns an object of the \linkS4class{H2OModelMetrics} subclass.
 #' @examples
 #' \dontrun{
@@ -1039,7 +1040,7 @@ h2o.feature_frequencies <- feature_frequencies.H2OModel
 #' h2o.performance(model = prostate_gbm_balanced, train = TRUE)
 #' }
 #' @export
-h2o.performance <- function(model, newdata=NULL, train=FALSE, valid=FALSE, xval=FALSE, data=NULL, auc_type="NONE", auuc_type="NONE") {
+h2o.performance <- function(model, newdata=NULL, train=FALSE, valid=FALSE, xval=FALSE, data=NULL, auc_type="NONE", auuc_type=NULL) {
 
   # data is now deprecated and the new arg name is newdata
   if (!is.null(data)) {
@@ -1056,12 +1057,13 @@ h2o.performance <- function(model, newdata=NULL, train=FALSE, valid=FALSE, xval=
   if(!is.logical(xval) || length(xval) != 1L || is.na(xval)) stop("`xval` must be TRUE or FALSE")
   if(sum(valid, xval, train) > 1) stop("only one of `train`, `valid`, and `xval` can be TRUE")
   if(!(auc_type %in% c("AUTO", "NONE", "MACRO_OVR", "WEIGHTED_OVR", "MACRO_OVO", "WEIGHTED_OVO"))) stop("`auc_type` must be \"AUTO\", \"NONE\", \"MACRO_OVR\", \"WEIGHTED_OVR\", \"MACRO_OVO\", or \"WEIGHTED_OVO\".")
+  if(!is.null(auuc_type) && !(auuc_type %in% c("AUTO", "GINI", "LIFT", "GAIN"))) stop("`auuc_type` must be \"AUTO\", \"GINI\", \"LIFT\" or \"GAIN\"." )  
 
   missingNewdata <- missing(newdata) || is.null(newdata)
   if( missingNewdata && auc_type != "NONE") {
     print("WARNING: The `auc_type` parameter is set but it is not used because the `newdata` parameter is NULL.")
   }
-  if( missingNewdata && auuc_type != "NONE") {
+  if( missingNewdata && !is.null(auuc_type)) {
     print("WARNING: The `auuc_type` parameter is set but it is not used because the `newdata` parameter is NULL.")
   }  
   if( !missingNewdata ) {
@@ -1078,9 +1080,9 @@ h2o.performance <- function(model, newdata=NULL, train=FALSE, valid=FALSE, xval=
     } else if(!is.null(model@parameters$auc_type) && model@parameters$auc_type != "NONE"){
         parms[["auc_type"]] <- model@parameters$auc_type
     }
-    if(auc_type != "NONE"){
+    if(!is.null(auuc_type)){
         parms[["auuc_type"]] <- auuc_type
-    } else if(!is.null(model@parameters$auuc_type) && model@parameters$auuc_type != "NONE"){
+    } else if(!is.null(model@parameters$auuc_type) && !is.null(model@parameters$auuc_type)){
         parms[["auuc_type"]] <- model@parameters$auuc_type
     }
     res <- .h2o.__remoteSend(method = "POST", .h2o.__MODEL_METRICS(model@model_id, newdata.id), .params = parms)