update test thresholds -> 0.9

Author: bensadeghi

test/classification/low_precision.jl

@@ -29,7 +29,7 @@ model = build_tree(
 preds = apply_tree(model, features)
 cm = confusion_matrix(labels, preds)
 @test typeof(preds) == Vector{Int32}
-@test cm.accuracy > 0.95
+@test cm.accuracy > 0.9
 
 n_subfeatures       = Int32(0)
 n_trees             = Int32(10)

test/classification/random.jl

@@ -20,7 +20,7 @@ print_tree(model, 3)
 model = build_tree(labels, features)
 preds = apply_tree(model, features)
 cm = confusion_matrix(labels, preds)
-@test cm.accuracy > 0.95
+@test cm.accuracy > 0.9
 @test typeof(preds) == Vector{Int}
 
 # test RNG param of trees
@@ -40,7 +40,7 @@ t3 = build_tree(labels, features, n_subfeatures; rng=mt)
 model = build_forest(labels, features)
 preds = apply_forest(model, features)
 cm = confusion_matrix(labels, preds)
-@test cm.accuracy > 0.95
+@test cm.accuracy > 0.9
 @test typeof(preds) == Vector{Int}
 
 n_subfeatures       = 3