-
## Proposal
Typically, interrupted time series (ITS) designs are univariate in that there is a single outcome variable. An existing example in the docs examines the causal impact of the onset of covi…
-
Regression (_e.g._ linear regression, logistic regression, poisson regression, etc) is a very important in machine learning. Many problems can be formulated in the form of (regularized) regression.
…
-
Classifiers have a `predict_proba` method that makes it possible to quantify probabilistic ally the certainty in the predictions for a given input `X_i`.
Currently most regressors in scikit-learn o…
-
The example in the README.md shows output columns
* [ ] `term`
* [ ] `estimate`
* [ ] `sd`
* [ ] `zscore`
* [ ] `lower`
* [ ] `upper`
* [ ] `pvalue`
I could not find doc for them other t…
-
From: Curry Cunningham
Sent: Thursday, June 24, 2021 8:03 PM
To: Brenner, Richard E (DFG)
Subject: Re: SECM Pink Salmon Forecast Meeting
Hi Rich,
Hope you are doing well, thanks for reach…
-
The Expectations framework currently allows you to specify the expected distribution of each variable independently. Here's a list of features that would be useful to see.
### Inter-variable depen…
-
In the context of geo testing... Let's say we have historical data of some KPI (such as sales, or customer sign ups) across multiple geographies. And we are considering running some geo testing on a s…
-
Feature to automate a variety of tasks associated with training a predictive machine learning model to generate market forecasts given a set of input signals. In general, this aims would be a sandbox …
-
This is something I definitely want to be central to the manuscript: How frequently do you need to measure to get good estimates on the parameters for the first order linear models?
I think a reaso…
-
## Keyword: out of distribution detection
There is no result
## Keyword: out-of-distribution detection
There is no result
## Keyword: expected calibration error
There is no result
## Keyword: overc…