88 lines
2.8 KiB
Python
88 lines
2.8 KiB
Python
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import csv
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import re
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import random
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import json
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# Prints ['Hey', 'you', 'what', 'are', 'you', 'doing', 'here']
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def make_dict(path):
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dict = {}
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with open(path) as in_file:
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for line in in_file:
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post = (line.split('\t')[0])
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for word in re.findall(r"[\w']+", post):
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if not word in dict:
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weight = round(random.random()%0.2-0.1,2)
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dict[word] = weight
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return dict
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def train_model(in_path, exp_path):
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dict = make_dict(in_path)
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w0 = 0.1
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lr = 0.0001
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with open(in_path) as in_file, open(exp_path) as exp_file:
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for in_line, exp_line in zip(in_file, exp_file):
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print("new post" + str(random.randint(0,10)))
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post = (in_line.split('\t')[0])
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delta = 1
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y=0
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y_plus = 0
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y_minus = 0
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while delta > 0.5:
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for word in re.findall(r"[\w']+", post):
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y += dict[word]
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y_plus += dict[word] + lr
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y_minus += dict[word] - lr
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delta = abs(int(exp_line) - y+w0)
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delta_minus = abs(int(exp_line) - y_minus+w0)
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delta_plus = abs(int(exp_line) - y_plus+w0)
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if delta_minus < delta:
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delta = delta_minus
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for word in re.findall(r"[\w']+", post):
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dict[word] = dict[word] - lr
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elif delta_plus < delta:
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delta = delta_plus
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for word in re.findall(r"[\w']+", post):
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dict[word] = dict[word] + lr
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else:
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break
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with open('dict.txt', 'w') as file:
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json.dump(dict, file)
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def predict(path):
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results = []
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with open('dict.txt', 'r') as file:
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dict = json.load(file)
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with open(path+"/in.tsv") as in_file:
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for in_line in in_file:
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print("new post" + str(random.randint(0,10)))
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post = (in_line.split('\t')[0])
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y=0
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for word in re.findall(r"[\w']+", post):
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if word in dict:
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y += dict[word]
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if y > 0.5:
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results.append("1")
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else:
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results.append("0")
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with open(path+"/out.tsv", 'wt') as tsvfile:
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tsv_writer = csv.writer(tsvfile, delimiter='\t')
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for i in results:
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tsv_writer.writerow(i)
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predict("test-A")
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def check_dev():
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with open("dev-0/out.tsv") as out_file, open("dev-0/expected.tsv") as exp_file:
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counter = 0
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positive = 0
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for out_line, exp_line in zip(out_file, exp_file):
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counter+=1
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if out_line == exp_line:
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positive += 1
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print(positive/counter)
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