# ('Title', 'categorical'): titles,
# ('Ticket_Code', 'categorical'): ticket_codes,
# ('Ticket_Val', 'continuous'): None,
}
target_var = ["Age", "continuous"]
# Only build a tree if necessary.
if build_tree:
# Build tree to predict age:
f = file("data/%s_age.csv" % filename, "r")
max_depth = 6
root = construct(f, ind_vars, target_var, max_depth)
f.close()
f = file("trees/age.tree", "w")
write_tree(root, f)
f.close()
# Trim tree: TODO
# Use tree to predict age:
# Compile list of independent variables used to predict target variable
tree = read_tree("trees/age.tree")
f = file("data/%s_no_age.csv" % filename, "r")
ind_vars[("PassengerId", "continuous")] = None
data = get_data(f, ind_vars)
var_dict = simplify_var_dict(ind_vars, None)
# Output target variable predictions to csv.
f = file("predictions/ages.csv", "w")
f.write("PassengerId,%s\n" % target_var[0])
pass
elif target_var and target_var[1] == 'continuous':
datum.append(float(line[var_dict[target_var[0]]]))
elif target_var:
raise Exception('Invalid variable type: %s' % target_var[1])
return datum
if __name__ == '__main__':
f = file('data/train_titles.csv', 'r')
ind_vars = {
('Sex', 'categorical'): ['male', 'female'],
('Pclass', 'categorical'): ['1', '2', '3'],
('Embarked', 'categorical'): ['S', 'C', 'Q'],
('Title', 'categorical'): titles,
('Ticket_Code', 'categorical'): ticket_codes,
('SibSp', 'continuous'): None,
('Parch', 'continuous'): None,
('Fare', 'continuous'): None,
('Ticket_Val', 'continuous'): None,
}
target_var = ['Survived', 'categorical', '0', '1']
max_depth = 100
tree = construct(f, ind_vars, target_var, max_depth)
f.close()
f = file('trees/temp.tree', 'w')
write_tree(tree, f)
f.close()
