from os.path import join, dirname import sys from languageflow.board import Board from languageflow.log import MultilabelLogger from languageflow.log.tfidf import TfidfLogger from load_data import load_dataset from model import sentiment data_file = join(dirname(dirname(dirname(dirname(__file__)))), "data", "fb_bank", "corpus", "test.xlsx") X_test, y_test = load_dataset(data_file) y_test = [tuple(item) for item in y_test] y_pred = sentiment(X_test) log_folder = join(dirname(__file__), "analyze") model_folder = join(dirname(__file__), "model") board = Board(log_folder=log_folder) MultilabelLogger.log(X_test, y_test, y_pred, log_folder=log_folder) TfidfLogger.log(model_folder=model_folder, log_folder=log_folder) board.serve(port=62010)
from os.path import join, dirname
from languageflow.board import Board
from languageflow.log import MultilabelLogger
import json
def load_data(file):
with open(file) as f:
content = json.load(open(file))
X, y = content["text"], content["labels"]
y = [tuple(item) for item in y]
return X, y
X, y1 = load_data("results/svc_full.json")
X, y2 = load_data("results/svc.json")
log_folder = join(dirname(__file__), "compare")
board = Board(log_folder=log_folder)
MultilabelLogger.log(X, y1, y2, log_folder=log_folder)
board.serve(port=62010)
from os.path import join, dirname
from languageflow.board import Board
from languageflow.log import MultilabelLogger
from exported.linearsvc import sentiment
from load_data import load_dataset
data = join(dirname(dirname(dirname(__file__))), "data", "vlsp2018", "corpus",
"hotel", "dev.xlsx")
X_dev, y_dev = load_dataset(data)
y_dev = [tuple(item) for item in y_dev]
y_pred = sentiment(X_dev)
log_folder = join(dirname(__file__), "analyze")
board = Board(log_folder=log_folder)
MultilabelLogger.log(X_dev, y_dev, y_pred, log_folder=log_folder)
# board.serve(port=62010)