我使用贝叶斯优化实现了运行Keras的以下代码:
def model_builder(hp):
NormLayer = Normalization()
NormLayer.adapt(X_train)
model = Sequential()
model.add(Input(shape=X_train.shape[1:]))
model.add(NormLayer)
for i in range(hp.Int('conv_layers',2,4)):
model.add(Conv1
哪个查询更快-(或者不重要)?
SELECT *
FROM students as s
INNER JOIN hallprefs as hp
ON s.studentid = hp.studentid
INNER JOIN halls as h
ON hp.hallid = h.hallid
或
SELECT *
FROM students as s
INNER JOIN hallprefs as hp
INNER JOIN halls as h
ON hp.hallid = h.hallid
AND s.studentid = hp.studentid
当然,
给出如下的数据帧: city district year price
0 bj cy 2018 NaN
1 bj cy 2019 6.0
2 sh hp 2018 4.0
3 sh hp 2019 3.0
4 bj hd 2018 7.0
5 bj hd 2019 NaN 如果price为NaN,我如何按city和district分组,并过滤行?谢谢。 我需要的输出如下所示: city district year price
0