# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# NOTE: This file is auto generated by the elixir code generator program.
# Do not edit this file manually.
defmodule GoogleApi.BigQuery.V2.Model.BinaryConfusionMatrix do
@moduledoc """
Confusion matrix for binary classification models.
## Attributes
* `accuracy` (*type:* `float()`, *default:* `nil`) - The fraction of predictions given the correct label.
* `f1Score` (*type:* `float()`, *default:* `nil`) - The equally weighted average of recall and precision.
* `falseNegatives` (*type:* `String.t`, *default:* `nil`) - Number of false samples predicted as false.
* `falsePositives` (*type:* `String.t`, *default:* `nil`) - Number of false samples predicted as true.
* `positiveClassThreshold` (*type:* `float()`, *default:* `nil`) - Threshold value used when computing each of the following metric.
* `precision` (*type:* `float()`, *default:* `nil`) - The fraction of actual positive predictions that had positive actual labels.
* `recall` (*type:* `float()`, *default:* `nil`) - The fraction of actual positive labels that were given a positive prediction.
* `trueNegatives` (*type:* `String.t`, *default:* `nil`) - Number of true samples predicted as false.
* `truePositives` (*type:* `String.t`, *default:* `nil`) - Number of true samples predicted as true.
"""
use GoogleApi.Gax.ModelBase
@type t :: %__MODULE__{
:accuracy => float() | nil,
:f1Score => float() | nil,
:falseNegatives => String.t() | nil,
:falsePositives => String.t() | nil,
:positiveClassThreshold => float() | nil,
:precision => float() | nil,
:recall => float() | nil,
:trueNegatives => String.t() | nil,
:truePositives => String.t() | nil
}
field(:accuracy)
field(:f1Score)
field(:falseNegatives)
field(:falsePositives)
field(:positiveClassThreshold)
field(:precision)
field(:recall)
field(:trueNegatives)
field(:truePositives)
end
defimpl Poison.Decoder, for: GoogleApi.BigQuery.V2.Model.BinaryConfusionMatrix do
def decode(value, options) do
GoogleApi.BigQuery.V2.Model.BinaryConfusionMatrix.decode(value, options)
end
end
defimpl Poison.Encoder, for: GoogleApi.BigQuery.V2.Model.BinaryConfusionMatrix do
def encode(value, options) do
GoogleApi.Gax.ModelBase.encode(value, options)
end
end