1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
|
# Authors: Gilles Louppe <g.louppe@gmail.com>
# Peter Prettenhofer <peter.prettenhofer@gmail.com>
# Brian Holt <bdholt1@gmail.com>
# Joel Nothman <joel.nothman@gmail.com>
# Arnaud Joly <arnaud.v.joly@gmail.com>
# Jacob Schreiber <jmschreiber91@gmail.com>
#
# License: BSD 3 clause
# See _criterion.pyx for implementation details.
from ._tree cimport DTYPE_t # Type of X
from ._tree cimport DOUBLE_t # Type of y, sample_weight
from ._tree cimport SIZE_t # Type for indices and counters
from ._tree cimport INT32_t # Signed 32 bit integer
from ._tree cimport UINT32_t # Unsigned 32 bit integer
cdef class Criterion:
# The criterion computes the impurity of a node and the reduction of
# impurity of a split on that node. It also computes the output statistics
# such as the mean in regression and class probabilities in classification.
# Internal structures
cdef const DOUBLE_t[:, ::1] y # Values of y
cdef const DOUBLE_t[:] sample_weight # Sample weights
cdef SIZE_t* samples # Sample indices in X, y
cdef SIZE_t start # samples[start:pos] are the samples in the left node
cdef SIZE_t pos # samples[pos:end] are the samples in the right node
cdef SIZE_t end
cdef SIZE_t n_outputs # Number of outputs
cdef SIZE_t n_samples # Number of samples
cdef SIZE_t n_node_samples # Number of samples in the node (end-start)
cdef double weighted_n_samples # Weighted number of samples (in total)
cdef double weighted_n_node_samples # Weighted number of samples in the node
cdef double weighted_n_left # Weighted number of samples in the left node
cdef double weighted_n_right # Weighted number of samples in the right node
# The criterion object is maintained such that left and right collected
# statistics correspond to samples[start:pos] and samples[pos:end].
# Methods
cdef int init(
self,
const DOUBLE_t[:, ::1] y,
const DOUBLE_t[:] sample_weight,
double weighted_n_samples,
SIZE_t* samples,
SIZE_t start,
SIZE_t end
) nogil except -1
cdef int reset(self) nogil except -1
cdef int reverse_reset(self) nogil except -1
cdef int update(self, SIZE_t new_pos) nogil except -1
cdef double node_impurity(self) nogil
cdef void children_impurity(
self,
double* impurity_left,
double* impurity_right
) nogil
cdef void node_value(
self,
double* dest
) nogil
cdef double impurity_improvement(
self,
double impurity_parent,
double impurity_left,
double impurity_right
) nogil
cdef double proxy_impurity_improvement(self) nogil
cdef class ClassificationCriterion(Criterion):
"""Abstract criterion for classification."""
cdef SIZE_t[::1] n_classes
cdef SIZE_t max_n_classes
cdef double[:, ::1] sum_total # The sum of the weighted count of each label.
cdef double[:, ::1] sum_left # Same as above, but for the left side of the split
cdef double[:, ::1] sum_right # Same as above, but for the right side of the split
cdef class RegressionCriterion(Criterion):
"""Abstract regression criterion."""
cdef double sq_sum_total
cdef double[::1] sum_total # The sum of w*y.
cdef double[::1] sum_left # Same as above, but for the left side of the split
cdef double[::1] sum_right # Same as above, but for the right side of the split
|
