feat: enhance multilingual support in LogisticRegression and its schema

Author: Irozuku

DashAI/back/models/scikit_learn/logistic_regression.py

@@ -7,6 +7,7 @@
     optimizer_int_field,
     schema_field,
 )
+from DashAI.back.core.utils import MultilingualString
 from DashAI.back.models.scikit_learn.sklearn_like_classifier import (
     SklearnLikeClassifier,
 )
@@ -25,7 +26,11 @@ class LogisticRegressionSchema(BaseSchema):
     penalty: schema_field(
         enum_field(enum=["l2", "l1", "elasticnet"]),
         placeholder="l2",
-        description="Specify the norm of the penalty",
+        description=MultilingualString(
+            en="Specify the norm of the penalty",
+            es="Especifica la norma de la penalización",
+        ),
+        alias=MultilingualString(en="Penalty", es="Penalización"),
     )  # type: ignore
     tol: schema_field(
         optimizer_float_field(ge=0.0),
@@ -35,7 +40,11 @@ class LogisticRegressionSchema(BaseSchema):
             "lower_bound": 0.0,
             "upper_bound": 5.0,
         },
-        description="Tolerance for stopping criteria.",
+        description=MultilingualString(
+            en="Tolerance for stopping criteria.",
+            es="Tolerancia para el criterio de detención.",
+        ),
+        alias=MultilingualString(en="Tolerance", es="Tolerancia"),
     )  # type: ignore
     C: schema_field(
         optimizer_float_field(gt=0.0),
@@ -45,8 +54,18 @@ class LogisticRegressionSchema(BaseSchema):
             "lower_bound": 1.0,
             "upper_bound": 7.0,
         },
-        description="Inverse of regularization strength, smaller values specify "
-        "stronger regularization. Must be a positive number.",
+        description=MultilingualString(
+            en=(
+                "Inverse of regularization strength, smaller values specify stronger "
+                "regularization. Must be a positive number."
+            ),
+            es=(
+                "Inverso de la fuerza de regularización, valores más pequeños "
+                "especifican una regularización más fuerte. Debe ser un número "
+                "positivo."
+            ),
+        ),
+        alias=MultilingualString(en="C", es="C"),
     )  # type: ignore
     max_iter: schema_field(
         optimizer_int_field(ge=50),
@@ -56,7 +75,11 @@ class LogisticRegressionSchema(BaseSchema):
             "lower_bound": 50,
             "upper_bound": 250,
         },
-        description="Maximum number of iterations taken for the solvers to converge.",
+        description=MultilingualString(
+            en=("Maximum number of iterations taken for the solvers to converge."),
+            es=("Número máximo de iteraciones para que los solucionadores converjan."),
+        ),
+        alias=MultilingualString(en="Max iterations", es="Máximas iteraciones"),
     )  # type: ignore
 
 
@@ -66,8 +89,14 @@ class LogisticRegression(
     """Scikit-learn's Logistic Regression wrapper for DashAI."""
 
     SCHEMA = LogisticRegressionSchema
-    DISPLAY_NAME: str = "Logistic Regression"
-    DESCRIPTION: str = "Linear model for classification using logistic function."
+    DISPLAY_NAME: str = MultilingualString(
+        en="Logistic Regression",
+        es="Regresión Logística",
+    )
+    DESCRIPTION: str = MultilingualString(
+        en="Linear model for classification using logistic function.",
+        es="Modelo lineal para clasificación usando la función logística.",
+    )
     COLOR: str = "#64B5F6"
     ICON: str = "TrendingUp"