[外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-h52WNhgg-1681785734231)(https://gitcode.net/apachecn/apachecn-dl-zh/-/raw/master/docs/handson-nlp-pt-1x/img/Formula_01_017.jpg)] [外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-JHkoIMCP-168178...
#!/usr/bin/env python3 words = ['forest', 'wood', 'sky', 'rock'] for word in reversed(words): print(word) word = 'forest' for e in reversed(word): print(e, end=' ') print() for e in reversed(range(1, 10, 2)): print(e) 在示例中,我们在列表,单词和范围上使用reversed(...
for epoch in range(n_epochs): h = net.init_hidden(batch_size) for inputs, labels in train_loader: step += 1 net.zero_grad() output, h = net(inputs) loss = criterion(output.squeeze(), labels.float()) loss.backward() nn.utils.clip_grad_norm(net.parameters(), clip) optimizer.st...
●range:指定直方图数据的上下界,默认包含绘图数据的最大值和最小值。 ●normed:是否将直方图的频数转换成频率。 ●weights:该参数可为每一个数据点设置权重。 ●cumulative:是否需要计算累计频数或频率。 ●bottom:可以为直方图的每个条形添加基准线,默认为0。 ●histtype:指定直方图的类型,默认为bar,除此还有barsta...
例如:“这里是RangeTransformer的简化代码。” 代码块设置如下: import openml dataset = openml.datasets.get_dataset(40536) X, y, categorical_indicator, _ = dataset.get_data( dataset_format='DataFrame', target=dataset.default_target_attribute ) 当我们希望引起您对代码块特定部分的注意时,相关行或...
defsome_function(a):return (a + 5) / 2my_formula = [some_function(i) for i in range(10)]print(my_formula)# [2, 3, 3, 4, 4, 5, 5, 6, 6, 7]最后，你还可以使用 ‘if’ 来过滤列表。在如下示例中，我们只保留能被2整除的数字：filtered = [i for i in range(20) if i%2==...
The binwidth is proportional to the interquartile range (IQR) and inversely proportional to cube root of a.size. Can be too conservative for small datasets, but is quite good for large datasets. The IQR is very robust to outliers.
def update(self, dt): n = len(self.vehicles) if n > 0: # Update first vehicle self.vehicles[0].update(None, dt) # Update other vehicles for i in range(1, n): lead = self.vehicles[i-1] self.vehicles[i].update(lead, dt 在Simulation类中添加一个update方法: def update(self): ...
import aeon import pandas as pd # 创建一个示例时间序列数据 data = {'date': pd.date_range(start='2022-01-01', periods=10, freq='D'), 'value': [10, 20, 15, 30, 25, 35, 40, 45, 50, 55]} df = pd.DataFrame(data) # 使用滑动窗口计算均值 window_size = 3 df['rolling_mean...
target_=np.array(target_train)'''重复多次随机分割样本集的训练取正确率平均值'''S=[]for i in range(1000): X_train, X_test, y_train, y_test= train_test_split(train_, target_, test_size=0.3) clf= DecisionTreeClassifier(class_weight='balanced',max_depth=2) ...