5 #ifndef NODE_FUZZY_FIXED_SPLIT
6 #define NODE_FUZZY_FIXED_SPLIT
8 #include "../n_train.h"
29 float gain(
const VectorXf& lsplit,
const VectorXf& rsplit,
30 bool classification=
false,
31 vector<float> unique_classes = vector<float>());
data holding X, y, and Z data
void eval_eqn(State &state)
Evaluates the node symbolically.
void set_threshold(ArrayXf &x, VectorXf &y, bool classification)
Uses a heuristic to set a splitting threshold.
float gain(const VectorXf &lsplit, const VectorXf &rsplit, bool classification=false, vector< float > unique_classes=vector< float >())
returns the gain of a split
void evaluate(const Data &data, State &state)
Evaluates the node and updates the state states.
NodeFuzzyFixedSplit * clone_impl() const override
NodeFuzzyFixedSplit * rnd_clone_impl() const override
float gini_impurity_index(const VectorXf &classes, vector< float > uc)
gini impurity of classes in classes
NLOHMANN_DEFINE_TYPE_NON_INTRUSIVE(NodeFuzzyFixedSplit< float >, name, otype, arity, complexity, visits, train, threshold, threshold_set) NLOHMANN_DEFINE_TYPE_NON_INTRUSIVE(NodeFuzzyFixedSplit< int >
contains various types of State actually used by feat