def check_internal_data(hierarhical_mlknn):
#----------------Functions needed to call tree_dfs_explorer---------------#
def stop_condition(result_data, input_data, curr_depth, max_depth):
if curr_depth == max_depth:
#PRINTER("[MlHierarchical: stop_condition]: either curr_labels is empty or curr_depth reached max:"+str(curr_labels)+", "+str(curr_depth))
return True
def process_node(node, input_data, curr_depth):
PRINTER("[MlHierarchical: process_node]: inspecting classifier on level: "+str(curr_depth))
PRINTER("[MlHierarchical: process_node]: printing first 2 records...")
i = 0
for rec in node.content.frecords:
PRINTER('[classify_stupid_no_exclude]: frecords '+str(rec))
i+=1
if i==2:
break
return None
def iterate_through_children(node, result_data):
for label in node.children.iterkeys():
PRINTER("[MlHierarchical: iterate_through_children]: looking for classification as: "+str(label)+".")
yield node.children[label]
def postprocess_result_data(x):
pass
#----------------End of Functions needed to call tree_dfs_explorer---------------#
import sys
sys.path.append(r'../')
from tools.tree_dfs_explorer import tree_dfs_explorer
tree_dfs_explorer(None, hierarhical_mlknn.mltree, hierarhical_mlknn.max_depth, 0, stop_condition,
process_node, iterate_through_children, postprocess_result_data)
def classify(self, sample):
'''
Classify using the classification tree. Return list of labels.
Note: the order of the resulting list is not significant.
'''
return tree_dfs_explorer(sample, self.mltree, self.max_depth, 0, self.stop_condition,
self.process_node, self.go_downwards, self.postprocess_result_data)
def classify(self, sample):
'''
Classify using the classification tree. Return list of labels.
Note: the order of the resulting list is not significant.
'''
return tree_dfs_explorer(sample, self.mltree, self.max_depth, 0,
self.stop_condition, self.process_node,
self.iterate_through_children,
self.postprocess_result_data)
def check_internal_data(hierarhical_mlknn):
#----------------Functions needed to call tree_dfs_explorer---------------#
def stop_condition(result_data, input_data, curr_depth, max_depth):
if curr_depth == max_depth:
#PRINTER("[MlHierarchical: stop_condition]: either curr_labels is empty or curr_depth reached max:"+str(curr_labels)+", "+str(curr_depth))
return True
def process_node(node, input_data, curr_depth):
PRINTER(
"[MlHierarchical: process_node]: inspecting classifier on level: "
+ str(curr_depth))
PRINTER("[MlHierarchical: process_node]: printing first 2 records...")
i = 0
for rec in node.content.frecords:
PRINTER('[classify_stupid_no_exclude]: frecords ' + str(rec))
i += 1
if i == 2:
break
return None
def iterate_through_children(node, result_data):
for label in node.children.iterkeys():
PRINTER(
"[MlHierarchical: iterate_through_children]: looking for classification as: "
+ str(label) + ".")
yield node.children[label]
def postprocess_result_data(x):
pass
#----------------End of Functions needed to call tree_dfs_explorer---------------#
import sys
sys.path.append(r'../')
from tools.tree_dfs_explorer import tree_dfs_explorer
tree_dfs_explorer(None, hierarhical_mlknn.mltree,
hierarhical_mlknn.max_depth, 0, stop_condition,
process_node, iterate_through_children,
postprocess_result_data)
def classify(self, sample):
'''
Classify using the classification tree. Return list of labels.
Note: the order of the resulting list is not significant.
'''
return tree_dfs_explorer(
sample, self.mltree, self.max_depth, 0,
lambda result_data, input_data, curr_depth, max_depth: self.
stop_condition(result_data, input_data, curr_depth, max_depth, self
.is_leaf_node), self.process_node,
self.go_downwards, self.postprocess_result_data)
