make_regression.hpp
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1 /*
2  * SPDX-FileCopyrightText: Copyright (c) 2019-2022, NVIDIA CORPORATION.
3  * SPDX-License-Identifier: Apache-2.0
4  */
5 
6 #pragma once
7 
8 #include <cstdint>
9 
10 namespace raft {
11 class handle_t;
12 }
13 
14 namespace ML {
15 namespace Datasets {
16 
47 void make_regression(const raft::handle_t& handle,
48  float* out,
49  float* values,
50  int64_t n_rows,
51  int64_t n_cols,
52  int64_t n_informative,
53  float* coef = nullptr,
54  int64_t n_targets = 1LL,
55  float bias = 0.0f,
56  int64_t effective_rank = -1LL,
57  float tail_strength = 0.5f,
58  float noise = 0.0f,
59  bool shuffle = true,
60  uint64_t seed = 0ULL);
61 
62 void make_regression(const raft::handle_t& handle,
63  double* out,
64  double* values,
65  int64_t n_rows,
66  int64_t n_cols,
67  int64_t n_informative,
68  double* coef = nullptr,
69  int64_t n_targets = 1LL,
70  double bias = 0.0,
71  int64_t effective_rank = -1LL,
72  double tail_strength = 0.5,
73  double noise = 0.0,
74  bool shuffle = true,
75  uint64_t seed = 0ULL);
76 
77 void make_regression(const raft::handle_t& handle,
78  float* out,
79  float* values,
80  int n_rows,
81  int n_cols,
82  int n_informative,
83  float* coef = nullptr,
84  int n_targets = 1LL,
85  float bias = 0.0f,
86  int effective_rank = -1LL,
87  float tail_strength = 0.5f,
88  float noise = 0.0f,
89  bool shuffle = true,
90  uint64_t seed = 0ULL);
91 
92 void make_regression(const raft::handle_t& handle,
93  double* out,
94  double* values,
95  int n_rows,
96  int n_cols,
97  int n_informative,
98  double* coef = nullptr,
99  int n_targets = 1LL,
100  double bias = 0.0,
101  int effective_rank = -1LL,
102  double tail_strength = 0.5,
103  double noise = 0.0,
104  bool shuffle = true,
105  uint64_t seed = 0ULL);
106 
107 } // namespace Datasets
108 } // namespace ML
ML::Datasets::make_regression
void make_regression(const raft::handle_t &handle, float *out, float *values, int64_t n_rows, int64_t n_cols, int64_t n_informative, float *coef=nullptr, int64_t n_targets=1LL, float bias=0.0f, int64_t effective_rank=-1LL, float tail_strength=0.5f, float noise=0.0f, bool shuffle=true, uint64_t seed=0ULL)
GPU-equivalent of sklearn.datasets.make_regression as documented at: https://scikit-learn....
ML::Solver::shuffle
void shuffle(std::vector< math_t > &rand_indices, std::mt19937 &g)
Definition: shuffle.h:24
ML
Definition: dbscan.hpp:18
raft
Definition: dbscan.hpp:14
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