generic ml fit, load_ml and save_ml update

Author: PondiB

meta/subtype-schemas.json

@@ -232,7 +232,7 @@
                 }
             }
         },
-        "mlm-model": {
+        "ml-model": {
             "type": "object",
             "subtype": "ml-model",
             "title": "Machine Learning Model",

proposals/load_ml_model.json

@@ -1,7 +1,7 @@
 {
     "id": "load_ml_model",
     "summary": "Load a ML model",
-    "description": "Loads a machine learning model from a STAC Item.\n\nSuch a model could be trained and saved as part of a previous batch job with processes such as  ``ml_fit_regr_random_forest()`` and ``save_ml_model()``.",
+    "description": "Loads a machine learning model from a STAC Item.\n\nSuch a model could be trained and saved as part of a previous batch job with processes such as  ``ml_fit()`` and ``save_ml_model()``.",
     "categories": [
         "machine learning",
         "import"
@@ -10,7 +10,7 @@
     "parameters": [
         {
             "name": "uri",
-            "description": "The STAC Item to load the machine learning model from. The STAC Item must implement the `mlm-model` extension.",
+            "description": "The STAC Item to load the machine learning model from. The STAC Item must implement the `ml-model` extension.",
             "schema": [
                 {
                     "title": "URL",
@@ -37,7 +37,7 @@
     },
     "links": [
         {
-            "href": "https://github.com/crim-ca/mlm-extension",
+            "href": "https://github.com/stac-extensions/mlm",
             "title": "Machine Learning Model STAC extension",
             "type": "text/html",
             "rel": "about"

proposals/ml_fit.json

@@ -0,0 +1,63 @@
+{
+    "id": "ml_fit",
+    "summary": "Train a machine learning model",
+    "description": "Executes the fit of a specified machine learning model based on training data. .\n\nThe function is generic and supports different machine learning models.",
+    "categories": [
+        "machine learning"
+    ],
+    "experimental": true,
+    "parameters": [
+        {
+            "name": "model",
+            "description": "The machine learning model to be trained. This should be an instance of a model that supports the `fit` method.",
+            "schema": {
+                "type": "object",
+                "subtype": "ml-model"
+            }
+        },
+        {
+            "name": "training_set",
+            "description": "The training set for the model, provided as a vector data cube. This set contains both the independent variables and the dependent variable that the model analyzes to learn patterns and relationships within the data.",
+            "schema": [
+                {
+                    "type": "object",
+                    "subtype": "datacube",
+                    "dimensions": [
+                        {
+                            "type": "geometry"
+                        },
+                        {
+                            "type": "bands"
+                        }
+                    ]
+                },
+                {
+                    "type": "object",
+                    "subtype": "datacube",
+                    "dimensions": [
+                        {
+                            "type": "geometry"
+                        },
+                        {
+                            "type": "other"
+                        }
+                    ]
+                }
+            ]
+        },
+        {
+            "name": "target",
+            "description": "The column in the training set that represents the dependent variable for model training.",
+            "schema": {
+                "type": "string"
+            }
+        }
+    ],
+    "returns": {
+        "description": "A trained model object that can be saved with `save_ml_model()` and restored with `load_ml_model()`.",
+        "schema": {
+            "type": "object",
+            "subtype": "ml-model"
+        }
+    }
+}

proposals/save_ml_model.json

@@ -1,7 +1,7 @@
 {
     "id": "save_ml_model",
     "summary": "Save a ML model",
-    "description": "Saves a machine learning model as part of a batch job.\n\nThe model will be accompanied by a separate STAC Item that implements the [mlm-model extension](https://github.com/crim-ca/mlm-extension).",
+    "description": "Saves a machine learning model as part of a batch job.\n\nThe model will be accompanied by a separate STAC Item that implements the [mlm-model extension](https://github.com/stac-extensions/mlm).",
     "categories": [
         "machine learning",
         "import"
@@ -13,7 +13,7 @@
             "description": "The data to store as a machine learning model.",
             "schema": {
                 "type": "object",
-                "subtype": "mlm-model"
+                "subtype": "ml-model"
             }
         },
         {
@@ -35,7 +35,7 @@
     },
     "links": [
         {
-            "href": "https://github.com/crim-ca/mlm-extension",
+            "href": "https://github.com/stac-extensions/mlm",
             "title": "Machine Learning Model STAC extension",
             "type": "text/html",
             "rel": "about"