GoOut | 一个出行游玩活动的APP -

You have to define the channel in a different way/can request it in a different way.

Have a look at the following code:

mck's suggestion of using 'features' from lr_preds works to get the metadata, it's unchanged. Thank you.

the column features should remain in the dataframelr_preds, maybe you can get it from that column instead?

In this code's block:

I can't spot any practical differences, no!

Looking at the generated bytecode shows that the two cases are more similar than you might think: both have a static initialiser, and a field.  The main difference is that in the object case those are in a new class and the field (INSTANCE) is public, while in the var case it's private and accessed through a getter method in a hidden class named …Kt.  (In practice, the getter will usually get optimised out anyway.)  That might affect the initialisation order, but that won't matter here.

At the language level, the object version will create a new subclass, while the val version won't — so you might see the latter as being slightly ‘purer’, though I can't see how that would matter to you.  And if you were calling from Java, the two cases would have different complications — though the question only mentioned Kotlin.

And the val version is very slightly shorter and simpler — only a tiny advantage, but in the absence of any other factors, brevity and simplicity are good things!

By the way, the question assumes that the configure() method is ‘fluent’, i.e. returns the object on which it's called.  But even if not, you can get the same effect by simply surrounding it in an apply() call.

If you want to type text in a ModalBottomSheet and get it in the underlying widget, just use the same TextEditingController in both, initializing and disposing it in your main widget.

Here is a working example:

I consulted this question internally,

Any sort of interaction - including get, create and update to Mobile App Channels through the API is not possible and gives 404. This notification channel cannot be used by non-Google internal API clients. As such, automation is not currently possible.

The Cloud Stackdriver Monitoring team is aware of this limitation, but it solving this issue is not on the priority list, hence there is no ETA for implementation any time soon.

There is a Issue Tracker regarding this topic, if you want to receive updates, please star the issue.

I would suggest learning about error metrics of linear regression models. RMSE would be a good start. This would give you some intuition as to why your approach doesn't work. In short you probably need a margin of error much larger than just the decimal points after the number.

Try rewriting your code to

if lab_test[b] >= predictions[b] * .8 and lab_test[b] <= predictions[b] * 1.2

to give yourself a 20 percent margin of error either direction and you'll see your 'accuracy' go up.

To understand why such a large margin of error is required, learn about RMSE and other error metrics, and how to minimize them.

http4k doesn't ship with a version of the OpenApi UI. You can easily ship a version of the UI though by:

1. unpacking the OpenApi UI into the src/main/resources/public folder
2. Using a static routing block to server the resources. There is an example of that here: https://github.com/http4k/http4k-by-example/blob/22dcc9a83c497253c29830d5bc981afa5fbbe4ff/src/main/kotlin/verysecuresystems/SecuritySystem.kt#L61

try adding