update params

proposals/ml_fit_class_svm.json

@@ -1,7 +1,7 @@
 {
     "id": "ml_fit_class_svm",
     "summary": "Train a Support Vector Machine classification model",
-    "description": "Executes the training of a Support Vector Machine classification model based on the provided training data. The Support Vector Machine classification model is a supervised machine learning algorithm used for binary and multi-class classification tasks.",
+    "description": "Executes the training of a Support Vector Machine classification model based on the provided training data. It is used for binary and multi-class classification tasks.",
     "categories": [
         "machine learning"
     ],
@@ -46,17 +46,16 @@
             "description": "Regularization parameter. It controls the trade-off between achieving a low training error and a low testing error. A smaller value will make the decision boundary smoother, while a larger value will allow the model to fit the training data more closely.",
             "schema": {
                 "type": "number",
-                "minimum": 0.0
+                "minimum": 0
             }
         },
         {
             "name": "gamma",
             "description": "Kernel coefficient for 'rbf', 'poly', and 'sigmoid'. A small value means a more flexible decision boundary, while a larger value means a more rigid boundary.",
             "optional": true,
-            "default": "auto",
             "schema": {
-                "type": ["number", "string"],
-                "minimum": 0.0
+                "type": "number",
+                "minimum": 0
             }
         },
         {
@@ -73,7 +72,7 @@
             "name": "coef0",
             "description": "Independent term in the 'poly' and 'sigmoid' kernel functions. Only used for 'poly' and 'sigmoid' kernels.",
             "optional": true,
-            "default": 0.0,
+            "default": 0,
             "schema": {
                 "type": "number"
             }