ppforest2::io::ModelStats Struct Reference

Per-iteration training statistics. More...

#include <EvaluateResult.hpp>

Public Member Functions
double	mean_te_error () const
double	mean_time () const
double	mean_tr_error () const
double	std_te_error () const
double	std_time () const
double	std_tr_error () const
EvaluateResult	summarize () const
	Produce an EvaluateResult summary from per-iteration data.
nlohmann::json	to_json () const
	Serialize to JSON including per-iteration breakdown.

Public Attributes
std::string	data_path
int	g = 0
	Number of groups (0 for regression).
types::Mode	mode = types::Mode::Classification
	Training mode.
int	n = 0
	Number of observations.
std::optional< int >	n_vars
int	p = 0
	Number of features.
std::optional< float >	p_vars
long	peak_rss_bytes = -1
int	size = 0
types::Vector< double >	te_error
types::Vector< double >	tr_error
types::Vector< long long >	tr_times
float	train_ratio = 0.7F

Detailed Description

Per-iteration training statistics.

Stores per-iteration timing and error vectors, plus the process-wide peak RSS. Provides mean/std accessors, an EvaluateResult summary, and full JSON serialization (including a per-iteration breakdown).

Member Function Documentation

mean_te_error()

double ppforest2::io::ModelStats::mean_te_error ( ) const

inline

mean_time()

double ppforest2::io::ModelStats::mean_time ( ) const

inline

mean_tr_error()

double ppforest2::io::ModelStats::mean_tr_error ( ) const

inline

std_te_error()

double ppforest2::io::ModelStats::std_te_error ( ) const

inline

std_time()

double ppforest2::io::ModelStats::std_time ( ) const

inline

std_tr_error()

double ppforest2::io::ModelStats::std_tr_error ( ) const

inline

summarize()

EvaluateResult ppforest2::io::ModelStats::summarize

(

)

const

Produce an EvaluateResult summary from per-iteration data.

to_json()

nlohmann::json ppforest2::io::ModelStats::to_json

(

)

const

Serialize to JSON including per-iteration breakdown.

Member Data Documentation

data_path

std::string ppforest2::io::ModelStats::data_path

g

int ppforest2::io::ModelStats::g = 0

Number of groups (0 for regression).

mode

types::Mode ppforest2::io::ModelStats::mode = types::Mode::Classification

Training mode.

n

int ppforest2::io::ModelStats::n = 0

Number of observations.

n_vars

std::optional<int> ppforest2::io::ModelStats::n_vars

p

int ppforest2::io::ModelStats::p = 0

Number of features.

p_vars

std::optional<float> ppforest2::io::ModelStats::p_vars

peak_rss_bytes

long ppforest2::io::ModelStats::peak_rss_bytes = -1

size

int ppforest2::io::ModelStats::size = 0

te_error

types::Vector<double> ppforest2::io::ModelStats::te_error

tr_error

types::Vector<double> ppforest2::io::ModelStats::tr_error

tr_times

types::Vector<long long> ppforest2::io::ModelStats::tr_times

train_ratio

float ppforest2::io::ModelStats::train_ratio = 0.7F

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The documentation for this struct was generated from the following file:

• core/src/io/EvaluateResult.hpp