<jupyter_start><jupyter_text>Comprobaciones<jupyter_code>y_predict = regr.predict(X_test)
rmse = np.sqrt(np.sum((y_test - y_predict)**2)/y_predict.shape[0])
print(rmse)
pos = [[140, 50, 40]]

regr.predict(pos)
a =0.60287883
b =1.6201514
c =-0.33788292

valorx= 80*(math.sin(5*b/12)+math.cos(5*c/12))*math.cos(21*a/40)
valory=80*(math.sin(5*b/12)+math.cos(5*c/12))*math.sin(21*a/40)
valorz=80*(math.cos(5*b/12)+math.sin(5*c/12))

print(valorx, valory, valorz)<jupyter_output>122.7862661996604 40.21521947617495 51.22780667157251
{'fraction_non_alphanumeric': 0.21062618595825428, 'fraction_numerical': 0.21821631878557876, 'mean_word_length': 7.380952380952381, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '469988', 'license': 'MIT', 'n_tokens_mistral': 332, 'n_tokens_neox': 263, 'n_words': 26, 'path': 'entrenamiento_red_neuronal.ipynb', 'repo_name': 'DiegoRev/rnn-robot-arm', 'size': '527'}