如何高效构建一个信息分类系统？

信息分类系统源码通常包括数据结构、算法和界面设计，用于高效管理和检索信息。

import os
import re
import jieba
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.naive_bayes import MultinomialNB
from sklearn.metrics import accuracy_score, confusion_matrix
def load_data(data_dir):
    labels = []
    contents = []
    for label in os.listdir(data_dir):
        label_dir = os.path.join(data_dir, label)
        if os.path.isdir(label_dir):
            for file in os.listdir(label_dir):
                file_path = os.path.join(label_dir, file)
                with open(file_path, 'r', encoding='utf8') as f:
                    content = f.read()
                    contents.append(content)
                    labels.append(label)
    return labels, contents
def preprocess_data(contents):
    processed_contents = []
    for content in contents:
        content = re.sub('[^u4e00u9fa5]+', '', content)  # 去除非中文字符
        words = jieba.cut(content)  # 分词
        processed_contents.append(' '.join(words))
    return processed_contents
def train_and_evaluate(X_train, X_test, y_train, y_test):
    vectorizer = CountVectorizer()
    X_train_vec = vectorizer.fit_transform(X_train)
    X_test_vec = vectorizer.transform(X_test)
    clf = MultinomialNB()
    clf.fit(X_train_vec, y_train)
    y_pred = clf.predict(X_test_vec)
    accuracy = accuracy_score(y_test, y_pred)
    cm = confusion_matrix(y_test, y_pred)
    return accuracy, cm
if __name__ == '__main__':
    data_dir = 'path/to/your/data'  # 替换为你的数据目录路径
    labels, contents = load_data(data_dir)
    processed_contents = preprocess_data(contents)
    X_train, X_test, y_train, y_test = train_test_split(processed_contents, labels, test_size=0.2, random_state=42)
    accuracy, cm = train_and_evaluate(X_train, X_test, y_train, y_test)
    print("Accuracy:", accuracy)
    print("Confusion Matrix:")
    print(cm)

这个源码首先加载数据，然后对文本内容进行预处理（去除非中文字符和分词），接着使用朴素贝叶斯分类器进行训练和评估，你需要将data_dir变量替换为你的数据目录路径，该目录下应该包含各个类别的子目录，每个子目录中包含属于该类别的文本文件。