Python AIND-手语识别

我正在GitHub上进行手语识别的工作

我对车型选择有一个问题。 当我在那里运行这个单元时

import warnings 
from hmmlearn.hmm import GaussianHMM

def train_a_word(word, num_hidden_states, features):
    warnings.filterwarnings("ignore", category=DeprecationWarning)
    training = asl.build_training(features)  
    X, lengths = training.get_word_Xlengths(word)
    model = GaussianHMM(n_components=num_hidden_states, n_iter=1000).fit(X, lengths)
    logL = model.score(X, lengths)
    return model, logL

demoword = 'BOOK'
model, logL = train_a_word(demoword, 3 , features=features_ground)
print("Number of states trained in model for {} is {}".format(demoword, model.n_components))
print("logL = {}".format(logL))

我有一个错误：

TypeError Traceback (most recent call last) in () 12  13 demoword = 'BOOK' ---> 14 model, 
  logL = train_a_word(demoword, 3 , features=features_ground) 15 print("Number of states 
  trained in model for {} is {}".format(demoword, model.n_components)) 
  16 print("logL = {}".format(logL)) in train_a_word(word, num_hidden_states, features) 
  7 training = asl.build_training(features) 8 X, lengths = training.get_word_Xlengths(word) 
  ----> 9 model = GaussianHMM(n_components=num_hidden_states, n_iter=1000).fit(X, lengths) 
  10 logL = model.score(X, lengths) 11 return model, logL

TypeError: fit() takes 2 positional arguments but 3 were given

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我想说的是，我们不应该修改这个单元格。

问题是由您的线路引起的

model = GaussianHMM(n_components=num_hidden_states, n_iter=1000).fit(X, lengths)

要解决此问题：
更改

fit（X，长度）

的

fit（X，长度=长度）

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尝试更新您的依赖项，尤其是hmmlearn和scikit learn。 您可以在此处找到完整的项目，以供将来参考：

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hello@codeiscool，我改变了

fit（X，length）

的

fit（X，length=length）

就像你建议的那样，然后我得到了一个新错误：fit（）得到了一个意外的关键字参数“length”