extrnalize train with dmatrix

src/scicloj/ml/xgboost.clj

@@ -251,17 +251,26 @@ subsample may be set to as low as 0.1 without loss of model accuracy. Note that
     (sparse-feature->dmatrix feature-ds target-ds sparse-column n-sparse-columns)
     (dataset->dmatrix feature-ds target-ds)))
 
-(defn- train
-  [feature-ds label-ds options]
+
+
+(defn- thaw-model
+  [model-data]
+  (-> (if (map? model-data)
+        (:model-data model-data)
+        model-data)
+      (ByteArrayInputStream.)
+      (XGBoost/loadModel)))
+
+
+
+(defn train-from-dmatrix
+  [train-dmat feature-cnames target-cnames options label-map objective]
   ;;XGBoost uses all cores so serialization here avoids over subscribing
   ;;the machine.
   (locking #'multiclass-objective?
-    (let [objective (options->objective options)
+    (let [
           sparse-column-or-nil (:sparse-column options)
-          train-dmat (->dmatrix feature-ds label-ds sparse-column-or-nil (:n-sparse-columns options))
           base-watches (or (:watches options) {})
-          feature-cnames (ds/column-names feature-ds)
-          target-cnames (ds/column-names label-ds)
           watches (->> base-watches
                        (reduce (fn  [^Map watches [k v]]
                                  (.put watches (ds-utils/column-safe-name k)
@@ -271,7 +280,7 @@ subsample may be set to as low as 0.1 without loss of model accuracy. Note that
                                         sparse-column-or-nil
                                         (:n-sparse-columns options)))
                                  watches)
-                               ;;Linked hash map to preserve order
+                                 ;;Linked hash map to preserve order
                                (LinkedHashMap.)))
           round (or (:round options) 25)
           early-stopping-round (or (when (:early-stopping-round options)
@@ -281,46 +290,41 @@ subsample may be set to as low as 0.1 without loss of model accuracy. Note that
                        (not (instance? LinkedHashMap (:watches options)))
                        (not= 0 early-stopping-round))
               (log/warn "Early stopping indicated but watches has undefined iteration order.
-Early stopping will always use the 'last' of the watches as defined by the iteration
-order of the watches map.  Consider using a java.util.LinkedHashMap for watches.
-https://github.com/dmlc/xgboost/blob/master/jvm-packages/xgboost4j/src/main/java/ml/dml
-c/xgboost4j/java/XGBoost.java#L208"))
+  Early stopping will always use the 'last' of the watches as defined by the iteration
+  order of the watches map.  Consider using a java.util.LinkedHashMap for watches.
+  https://github.com/dmlc/xgboost/blob/master/jvm-packages/xgboost4j/src/main/java/ml/dml
+  c/xgboost4j/java/XGBoost.java#L208"))
           watch-names (->> base-watches
                            (map-indexed (fn [idx [k v]]
                                           [idx k]))
                            (into {}))
-          label-map (when (multiclass-objective? objective)
-                      (ds-mod/inference-target-label-map label-ds))
-          cleaned-options 
+          cleaned-options
           (->
            (dissoc options :model-type :watches)
            (assoc :objective objective))
           params (->>  cleaned-options
-                      ;;Adding in some defaults
+                        ;;Adding in some defaults
                        (merge
-                        {
-                          :alpha 0.0
-                          :eta 0.3
-                          :lambda 1.0
-                          :max-depth 6
-                          :subsample 0.87
-
-                         }
-
+                        {:alpha 0.0
+                         :eta 0.3
+                         :lambda 1.0
+                         :max-depth 6
+                         :subsample 0.87}
+
                         cleaned-options
                         (when label-map
                           {:num-class (count label-map)}))
                        (map (fn [[k v]]
                               (when v
-                                [(s/replace (name k) "-" "_" ) v])))
+                                [(s/replace (name k) "-" "_") v])))
 
                        (remove nil?)
                        (into {}))
           ^"[[F" metrics-data (when-not (empty? watches)
                                 (->> (repeatedly (count watches)
                                                  #(float-array round))
                                      (into-array)))
-
+          _ (println :params params)
           ^Booster model (XGBoost/train train-dmat params
                                         (long round)
                                         (or watches {}) metrics-data nil nil
@@ -340,13 +344,16 @@ c/xgboost4j/java/XGBoost.java#L208"))
                (ds/->>dataset {:dataset-name :metrics}))})))))
 
 
-(defn- thaw-model
-  [model-data]
-  (-> (if (map? model-data)
-        (:model-data model-data)
-        model-data)
-      (ByteArrayInputStream.)
-      (XGBoost/loadModel)))
+(defn train [feature-ds label-ds options]
+  (let [sparse-column-or-nil (:sparse-column options)
+        feature-cnames (ds/column-names feature-ds)
+        target-cnames (ds/column-names label-ds)
+        train-dmat (->dmatrix feature-ds label-ds sparse-column-or-nil (:n-sparse-columns options))
+        objective (options->objective options)
+
+        label-map (when (multiclass-objective? objective)
+                    (ds-mod/inference-target-label-map label-ds))]
+    (train-from-dmatrix train-dmat feature-cnames target-cnames options label-map objective)))
 
 
 (defn- predict