1// Code generated by protoc-gen-go. DO NOT EDIT.
2// source: google/cloud/automl/v1beta1/regression.proto
3
4package automl
5
6import (
7	fmt "fmt"
8	math "math"
9
10	proto "github.com/golang/protobuf/proto"
11	_ "google.golang.org/genproto/googleapis/api/annotations"
12)
13
14// Reference imports to suppress errors if they are not otherwise used.
15var _ = proto.Marshal
16var _ = fmt.Errorf
17var _ = math.Inf
18
19// This is a compile-time assertion to ensure that this generated file
20// is compatible with the proto package it is being compiled against.
21// A compilation error at this line likely means your copy of the
22// proto package needs to be updated.
23const _ = proto.ProtoPackageIsVersion3 // please upgrade the proto package
24
25// Metrics for regression problems.
26type RegressionEvaluationMetrics struct {
27	// Output only. Root Mean Squared Error (RMSE).
28	RootMeanSquaredError float32 `protobuf:"fixed32,1,opt,name=root_mean_squared_error,json=rootMeanSquaredError,proto3" json:"root_mean_squared_error,omitempty"`
29	// Output only. Mean Absolute Error (MAE).
30	MeanAbsoluteError float32 `protobuf:"fixed32,2,opt,name=mean_absolute_error,json=meanAbsoluteError,proto3" json:"mean_absolute_error,omitempty"`
31	// Output only. Mean absolute percentage error. Only set if all ground truth
32	// values are are positive.
33	MeanAbsolutePercentageError float32 `protobuf:"fixed32,3,opt,name=mean_absolute_percentage_error,json=meanAbsolutePercentageError,proto3" json:"mean_absolute_percentage_error,omitempty"`
34	// Output only. R squared.
35	RSquared float32 `protobuf:"fixed32,4,opt,name=r_squared,json=rSquared,proto3" json:"r_squared,omitempty"`
36	// Output only. Root mean squared log error.
37	RootMeanSquaredLogError float32  `protobuf:"fixed32,5,opt,name=root_mean_squared_log_error,json=rootMeanSquaredLogError,proto3" json:"root_mean_squared_log_error,omitempty"`
38	XXX_NoUnkeyedLiteral    struct{} `json:"-"`
39	XXX_unrecognized        []byte   `json:"-"`
40	XXX_sizecache           int32    `json:"-"`
41}
42
43func (m *RegressionEvaluationMetrics) Reset()         { *m = RegressionEvaluationMetrics{} }
44func (m *RegressionEvaluationMetrics) String() string { return proto.CompactTextString(m) }
45func (*RegressionEvaluationMetrics) ProtoMessage()    {}
46func (*RegressionEvaluationMetrics) Descriptor() ([]byte, []int) {
47	return fileDescriptor_b0fa6250b0d4b440, []int{0}
48}
49
50func (m *RegressionEvaluationMetrics) XXX_Unmarshal(b []byte) error {
51	return xxx_messageInfo_RegressionEvaluationMetrics.Unmarshal(m, b)
52}
53func (m *RegressionEvaluationMetrics) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
54	return xxx_messageInfo_RegressionEvaluationMetrics.Marshal(b, m, deterministic)
55}
56func (m *RegressionEvaluationMetrics) XXX_Merge(src proto.Message) {
57	xxx_messageInfo_RegressionEvaluationMetrics.Merge(m, src)
58}
59func (m *RegressionEvaluationMetrics) XXX_Size() int {
60	return xxx_messageInfo_RegressionEvaluationMetrics.Size(m)
61}
62func (m *RegressionEvaluationMetrics) XXX_DiscardUnknown() {
63	xxx_messageInfo_RegressionEvaluationMetrics.DiscardUnknown(m)
64}
65
66var xxx_messageInfo_RegressionEvaluationMetrics proto.InternalMessageInfo
67
68func (m *RegressionEvaluationMetrics) GetRootMeanSquaredError() float32 {
69	if m != nil {
70		return m.RootMeanSquaredError
71	}
72	return 0
73}
74
75func (m *RegressionEvaluationMetrics) GetMeanAbsoluteError() float32 {
76	if m != nil {
77		return m.MeanAbsoluteError
78	}
79	return 0
80}
81
82func (m *RegressionEvaluationMetrics) GetMeanAbsolutePercentageError() float32 {
83	if m != nil {
84		return m.MeanAbsolutePercentageError
85	}
86	return 0
87}
88
89func (m *RegressionEvaluationMetrics) GetRSquared() float32 {
90	if m != nil {
91		return m.RSquared
92	}
93	return 0
94}
95
96func (m *RegressionEvaluationMetrics) GetRootMeanSquaredLogError() float32 {
97	if m != nil {
98		return m.RootMeanSquaredLogError
99	}
100	return 0
101}
102
103func init() {
104	proto.RegisterType((*RegressionEvaluationMetrics)(nil), "google.cloud.automl.v1beta1.RegressionEvaluationMetrics")
105}
106
107func init() {
108	proto.RegisterFile("google/cloud/automl/v1beta1/regression.proto", fileDescriptor_b0fa6250b0d4b440)
109}
110
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136