Fix remaining Classification metrics doctests for the f32 inspect change

Pure formatting, same values, shorter f32 representation. Same class
of miss as LedoitWolf/ShrunkCovariance: single-occurrence values
further down a doctest with a repeated literal elsewhere in the file
(0.6000000238418579 also appears as a Nx.f32() input argument
elsewhere, left untouched).

Author: RicardoSantos-99

lib/scholar/metrics/classification.ex

@@ -680,17 +680,17 @@ defmodule Scholar.Metrics.Classification do
       iex> Scholar.Metrics.Classification.fbeta_score(y_true, y_pred, Nx.u32(2), num_classes: 3, average: :macro)
       #Nx.Tensor<
         f32
-        0.6157407760620117
+        0.6157408
       >
       iex> Scholar.Metrics.Classification.fbeta_score(y_true, y_pred, Nx.u32(2), num_classes: 3, average: :weighted)
       #Nx.Tensor<
         f32
-        0.5958333611488342
+        0.59583336
       >
       iex> Scholar.Metrics.Classification.fbeta_score(y_true, y_pred, Nx.f32(0.5), num_classes: 3, average: :micro)
       #Nx.Tensor<
         f32
-        0.6000000238418579
+        0.6
       >
       iex> Scholar.Metrics.Classification.fbeta_score(Nx.tensor([1, 0, 1, 0]), Nx.tensor([0, 1, 0, 1]), Nx.tensor(0.5), num_classes: 2, average: :none)
       #Nx.Tensor<
@@ -864,12 +864,12 @@ defmodule Scholar.Metrics.Classification do
       iex> Scholar.Metrics.Classification.f1_score(y_true, y_pred, num_classes: 3, average: :weighted)
       #Nx.Tensor<
         f32
-        0.6399999856948853
+        0.64
       >
       iex> Scholar.Metrics.Classification.f1_score(y_true, y_pred, num_classes: 3, average: :micro)
       #Nx.Tensor<
         f32
-        0.6000000238418579
+        0.6
       >
       iex> Scholar.Metrics.Classification.f1_score(Nx.tensor([1, 0, 1, 0]), Nx.tensor([0, 1, 0, 1]), num_classes: 2, average: :none)
       #Nx.Tensor<