Wording improvements from #396

Author: m-mohr

proposals/predict_dl_model.json

@@ -1,7 +1,7 @@
 {
     "id": "predict_dl_model",
-    "summary": "Predict values values using a DL model",
-    "description": "Applies a machine learning model to a data cube and predicts a values/classes for it. This process can be used as process in ``apply_neighborhood()`` to specify the patch size and overlap.",
+    "summary": "Predict values values using DL",
+    "description": "Applies a machine learning model to a data cube of input features and predicts output values or classes for it. This process can be used as process in ``apply_neighborhood()`` to specify the patch size and overlap.",
     "categories": [
         "deep learning",
         "machine learning"
@@ -10,15 +10,15 @@
     "parameters": [
         {
             "name": "data",
-            "description": "The input data cube.",
+            "description": "The data cube containing the input features.",
             "schema": {
                 "type": "object",
                 "subtype": "datacube"
             }
         },
         {
             "name": "model",
-            "description": "A DL model that can be trained with one of the DL `fit_*` processes.",
+            "description": "A DL model that was trained with one of the DL training processes.",
             "schema": {
                 "type": "object",
                 "subtype": "ml-model"

proposals/predict_ml_model.json

@@ -1,23 +1,23 @@
 {
     "id": "predict_ml_model",
-    "summary": "Predict values values using a ML model",
-    "description": "Applies a machine learning model to a datacube and predicts values/classes for it.",
+    "summary": "Predict classification or regression values using ML",
+    "description": "Applies a machine learning model to a data cube of input features and predicts output values or classes for it.",
     "categories": [
         "machine learning"
     ],
     "experimental": true,
     "parameters": [
         {
             "name": "data",
-            "description": "The input data cube.",
+            "description": "The data cube containing the input features.",
             "schema": {
                 "type": "object",
                 "subtype": "datacube"
             }
         },
         {
             "name": "model",
-            "description": "A ML model that can be trained with one of the ML processes such as ``fit_class_random_forest()``.",
+            "description": "A ML model that was trained with one of the ML training processes such as ``fit_class_random_forest()``.",
             "schema": {
                 "type": "object",
                 "subtype": "ml-model"

proposals/predict_ml_model_probabilities.json

@@ -1,23 +1,23 @@
 {
     "id": "predict_ml_model_probabilities",
-    "summary": "Predict class probabilities using a ML model",
-    "description": "Applies a machine learning model to a data cube and predicts (class) probabilities.",
+    "summary": "Predict class probabilities using ML",
+    "description": "Applies a machine learning model to a data cube of input features and predicts the probabilities of the output classes.",
     "categories": [
         "machine learning"
     ],
     "experimental": true,
     "parameters": [
         {
             "name": "data",
-            "description": "The input data cube.",
+            "description": "The data cube containing the input features.",
             "schema": {
                 "type": "object",
                 "subtype": "datacube"
             }
         },
         {
             "name": "model",
-            "description": "A ML model that can be trained with one of the ML processes such as ``fit_regr_random_forest()``.",
+            "description": "A ML model that was trained with one of the ML training processes such as ``fit_regr_random_forest()``.",
             "schema": {
                 "type": "object",
                 "subtype": "ml-model"