Rename predict_proba to predict_probability

msluszniak · May 14, 2024 · 322687a · 322687a
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commit 322687a
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Showing 4 changed files with 13 additions and 13 deletions.
diff --git a/lib/scholar/neighbors/k_nearest_neighbors.ex b/lib/scholar/neighbors/k_nearest_neighbors.ex
@@ -224,15 +224,15 @@ defmodule Scholar.Neighbors.KNearestNeighbors do
       iex> x = Nx.tensor([[1, 2], [2, 4], [1, 3], [2, 5]])
       iex> y = Nx.tensor([1, 0, 1, 1])
       iex> model = Scholar.Neighbors.KNearestNeighbors.fit(x, y, num_classes: 2)
-      iex> Scholar.Neighbors.KNearestNeighbors.predict_proba(model, Nx.tensor([[1.9, 4.3], [1.1, 2.0]]))
+      iex> Scholar.Neighbors.KNearestNeighbors.predict_probability(model, Nx.tensor([[1.9, 4.3], [1.1, 2.0]]))
       Nx.tensor(
         [
           [0.75, 0.25],
           [0.75, 0.25]
         ]
       )
   """
-  deftransform predict_proba(
+  deftransform predict_probability(
                  %__MODULE__{
                    task: :classification
                  } = model,

diff --git a/lib/scholar/neighbors/radius_nearest_neighbors.ex b/lib/scholar/neighbors/radius_nearest_neighbors.ex
@@ -180,7 +180,7 @@ defmodule Scholar.Neighbors.RadiusNearestNeighbors do
   defn predict(%__MODULE__{labels: labels, weights: weights, task: task} = model, x) do
     case task do
       :classification ->
-        {probabilities, outliers_mask} = predict_proba(model, x)
+        {probabilities, outliers_mask} = predict_probability(model, x)
         results = Nx.argmax(probabilities, axis: 1)
         Nx.select(outliers_mask, -1, results)
 
@@ -235,7 +235,7 @@ defmodule Scholar.Neighbors.RadiusNearestNeighbors do
       iex> x = Nx.tensor([[1, 2], [2, 4], [1, 3], [2, 5]])
       iex> y = Nx.tensor([1, 0, 1, 1])
       iex> model = Scholar.Neighbors.RadiusNearestNeighbors.fit(x, y, num_classes: 2)
-      iex> Scholar.Neighbors.RadiusNearestNeighbors.predict_proba(model, Nx.tensor([[1.9, 4.3], [1.1, 2.0]]))
+      iex> Scholar.Neighbors.RadiusNearestNeighbors.predict_probability(model, Nx.tensor([[1.9, 4.3], [1.1, 2.0]]))
       {Nx.tensor(
         [
           [0.5, 0.5],
@@ -246,7 +246,7 @@ defmodule Scholar.Neighbors.RadiusNearestNeighbors do
         [0, 0], type: :u8
       )}
   """
-  deftransform predict_proba(%__MODULE__{task: :classification} = model, x) do
+  deftransform predict_probability(%__MODULE__{task: :classification} = model, x) do
     predict_proba_n(model, x)
   end
 

diff --git a/test/scholar/neighbors/k_nearest_neighbors_test.exs b/test/scholar/neighbors/k_nearest_neighbors_test.exs
@@ -140,7 +140,7 @@ defmodule Scholar.Neighbors.KNearestNeighborsTest do
   describe "predict_proba" do
     test "predict_proba with default values" do
       model = KNearestNeighbors.fit(x(), y(), num_classes: 2, num_neighbors: 3)
-      predictions = KNearestNeighbors.predict_proba(model, x_pred())
+      predictions = KNearestNeighbors.predict_probability(model, x_pred())
 
       assert_all_close(
         predictions,
@@ -157,7 +157,7 @@ defmodule Scholar.Neighbors.KNearestNeighborsTest do
       model =
         KNearestNeighbors.fit(x(), y(), num_classes: 2, num_neighbors: 3, weights: :distance)
 
-      predictions = KNearestNeighbors.predict_proba(model, x_pred())
+      predictions = KNearestNeighbors.predict_probability(model, x_pred())
 
       assert_all_close(
         predictions,
@@ -179,7 +179,7 @@ defmodule Scholar.Neighbors.KNearestNeighborsTest do
           metric: {:minkowski, 1.5}
         )
 
-      predictions = KNearestNeighbors.predict_proba(model, x_pred())
+      predictions = KNearestNeighbors.predict_probability(model, x_pred())
 
       assert_all_close(
         predictions,
@@ -198,7 +198,7 @@ defmodule Scholar.Neighbors.KNearestNeighborsTest do
       model =
         KNearestNeighbors.fit(x(), y(), num_classes: 2, num_neighbors: 3, weights: :distance)
 
-      predictions = KNearestNeighbors.predict_proba(model, x_pred)
+      predictions = KNearestNeighbors.predict_probability(model, x_pred)
 
       assert_all_close(
         predictions,

diff --git a/test/scholar/neighbors/radius_nearest_neighbors_test.exs b/test/scholar/neighbors/radius_nearest_neighbors_test.exs
@@ -143,7 +143,7 @@ defmodule Scholar.Neighbors.RadiusNearestNeighborsTest do
   describe "predict_proba" do
     test "predict_proba with default values except radius set to 10" do
       model = RadiusNearestNeighbors.fit(x(), y(), num_classes: 2, radius: 10)
-      {predictions, outliers_mask} = RadiusNearestNeighbors.predict_proba(model, x_pred())
+      {predictions, outliers_mask} = RadiusNearestNeighbors.predict_probability(model, x_pred())
 
       assert_all_close(
         predictions,
@@ -156,7 +156,7 @@ defmodule Scholar.Neighbors.RadiusNearestNeighborsTest do
     test "predict_proba with weights set to :distance" do
       model = RadiusNearestNeighbors.fit(x(), y(), num_classes: 2, radius: 10, weights: :distance)
 
-      {predictions, outliers_mask} = RadiusNearestNeighbors.predict_proba(model, x_pred())
+      {predictions, outliers_mask} = RadiusNearestNeighbors.predict_probability(model, x_pred())
 
       assert_all_close(
         predictions,
@@ -180,7 +180,7 @@ defmodule Scholar.Neighbors.RadiusNearestNeighborsTest do
           metric: {:minkowski, 1.5}
         )
 
-      {predictions, outliers_mask} = RadiusNearestNeighbors.predict_proba(model, x_pred())
+      {predictions, outliers_mask} = RadiusNearestNeighbors.predict_probability(model, x_pred())
 
       assert_all_close(
         predictions,
@@ -200,7 +200,7 @@ defmodule Scholar.Neighbors.RadiusNearestNeighborsTest do
 
       model = RadiusNearestNeighbors.fit(x(), y(), num_classes: 2, radius: 10, weights: :distance)
 
-      {predictions, outliers_mask} = RadiusNearestNeighbors.predict_proba(model, x_pred)
+      {predictions, outliers_mask} = RadiusNearestNeighbors.predict_probability(model, x_pred)
 
       assert_all_close(
         predictions,