ppforest2 v0.1.0
Projection Pursuit Decision Trees and Random Forests
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EvaluateParams.hpp
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1
5#pragma once
6
7#include <string>
8
9namespace ppforest2::cli {
12 std::string format;
13 int rows = 1000;
14 int cols = 10;
15 int n_groups = 2;
16 float mean = 100.0f;
17 float mean_separation = 50.0f;
18 float sd = 10.0f;
19 };
20
28 bool enabled = true;
29 int warmup = 0;
30 float cv = 0.05f;
31 int min = 10;
32 int window = 3;
33 int max = 200;
34 };
35
38 float train_ratio = 0.7;
39 int iterations = 1;
40 std::string export_path;
41 };
42}
Command-line interface: argument parsing, subcommands, and benchmark/evaluation orchestration.
Definition Benchmark.hpp:22
Convergence and iteration control (evaluate + benchmark).
Definition EvaluateParams.hpp:27
int window
Consecutive checks below threshold before stopping.
Definition EvaluateParams.hpp:32
int warmup
Warmup iterations discarded before measuring.
Definition EvaluateParams.hpp:29
int min
Minimum iterations before checking convergence.
Definition EvaluateParams.hpp:31
bool enabled
Adaptive stopping (default on; -i disables).
Definition EvaluateParams.hpp:28
int max
Hard upper bound on iterations.
Definition EvaluateParams.hpp:33
float cv
CV target (e.g. 0.05 = stop when std < 5% of mean).
Definition EvaluateParams.hpp:30
Evaluate-specific options.
Definition EvaluateParams.hpp:37
float train_ratio
Definition EvaluateParams.hpp:38
std::string export_path
Definition EvaluateParams.hpp:40
int iterations
Definition EvaluateParams.hpp:39
Simulation data source options.
Definition EvaluateParams.hpp:11
float sd
Definition EvaluateParams.hpp:18
int cols
Definition EvaluateParams.hpp:14
int rows
Definition EvaluateParams.hpp:13
float mean
Definition EvaluateParams.hpp:16
int n_groups
Definition EvaluateParams.hpp:15
float mean_separation
Definition EvaluateParams.hpp:17
std::string format
Definition EvaluateParams.hpp:12