从模糊名称匹配与机器学习 python 代码中获取错误

Question

我看到了这个博客（https://towardsdatascience.com/fuzzy-name -matching-with-machine-learning-f09895dce7b4）及其 Github 页面 (https://github.com/Christopher-Thornton/hmni），我按照安装设置进行操作并得到我的 pycharm 控制台中出现以下错误。错误屏幕截图随本文一起附上。请帮助我，因为我正在尝试学习 python

这是我的 Pycharm IDE 代码，看起来像

import hmni
matcher = hmni.Matcher(model='latin')

matcher.similarity('Alan', 'Al')
# 0.6838303319889133
matcher.similarity('Alan', 'Al', prob=False)
# 1
matcher.similarity('Alan Turing', 'Al Turing', surname_first=False)
# 0.68383033198891

,

Full Error list



/Users/user/folder/venv/bin/python /Users/user/folder/main.py
/Users/user/folder/venv/lib/python3.8/site-packages/sklearn/base.py:329: UserWarning: Trying to unpickle estimator MaxAbsScaler from version 0.23.1 when using version 1.0.2. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations
  warnings.warn(
/Users/user/folder/venv/lib/python3.8/site-packages/sklearn/base.py:329: UserWarning: Trying to unpickle estimator MinMaxScaler from version 0.23.1 when using version 1.0.2. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations
  warnings.warn(
/Users/user/folder/venv/lib/python3.8/site-packages/sklearn/base.py:329: UserWarning: Trying to unpickle estimator DecisionTreeClassifier from version 0.23.1 when using version 1.0.2. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations
  warnings.warn(
/Users/user/folder/venv/lib/python3.8/site-packages/sklearn/base.py:329: UserWarning: Trying to unpickle estimator RandomForestClassifier from version 0.23.1 when using version 1.0.2. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations
  warnings.warn(
/Users/user/folder/venv/lib/python3.8/site-packages/sklearn/base.py:329: UserWarning: Trying to unpickle estimator Pipeline from version 0.23.1 when using version 1.0.2. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations
  warnings.warn(
/Users/user/folder/venv/lib/python3.8/site-packages/sklearn/base.py:329: UserWarning: Trying to unpickle estimator LogisticRegression from version 0.23.1 when using version 1.0.2. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations
  warnings.warn(
Traceback (most recent call last):
  File "/Users/user/folder/main.py", line 8, in <module>
    matcher.similarity('Alan', 'Al')
  File "/Users/user/folder/venv/lib/python3.8/site-packages/hmni/matcher.py", line 266, in similarity
    sim = self.meta_inf(pair, features)
  File "/Users/user/folder/venv/lib/python3.8/site-packages/hmni/matcher.py", line 418, in meta_inf
    meta_features[0] = self.base_model_inf(base_features)
  File "/Users/user/folder/venv/lib/python3.8/site-packages/hmni/matcher.py", line 413, in base_model_inf
    y_pred = self.baseModel.predict_proba(x.reshape(1, -1))[0, 1]
  File "/Users/user/folder/venv/lib/python3.8/site-packages/sklearn/utils/metaestimators.py", line 113, in <lambda>
    out = lambda *args, **kwargs: self.fn(obj, *args, **kwargs)  # noqa
  File "/Users/user/folder/venv/lib/python3.8/site-packages/sklearn/pipeline.py", line 535, in predict_proba
    Xt = transform.transform(Xt)
  File "/Users/user/folder/venv/lib/python3.8/site-packages/sklearn/preprocessing/_data.py", line 506, in transform
    if self.clip:
AttributeError: 'MinMaxScaler' object has no attribute 'clip'

屏幕截图附在此处。请帮助我，我的预期结果是打印相似度分数，如 GitHub 页面所示