Jeff Levesque

With the adjusted port `9595`, as well as using `token = login.json()`, we receive a `timeout`: ```bash root@ubuntu-xenial:/vagrant# python3 test.py Traceback (most recent call last): File "/usr/lib/python3/dist-packages/urllib3/connection.py", line 137, in...

Our problems need to be further investigated based on the following: ```bash root@ubuntu-xenial:/vagrant# nmap -sS -p8585 xx.xx.xx.xx Starting Nmap 7.01 ( https://nmap.org ) at 2018-09-29 22:01 UTC Nmap scan report...

We sent a `POST` request from the `nginx-api`, to the `webserver-api` container: ```python >>> import requests >>> requests.post('http://webserver-api:6001/login', headers={'Content-Type': 'application/json'}, data={'user[login]': 'jeff1evesque', 'user[password]': 'password123'}, verify=False) >>> requests.post('http://webserver-api:6001/login', headers={'Content-Type': 'application/json'}, data={'user[login]':...

Posting from the `nginx-api`, to the `webserver-api` container, without `headers`: ```python >>> requests.post('http://webserver-api:6001/login', data={'user[login]': 'jeff1evesque', 'user[password]': 'password123'}) ```

Even after executing the above, no logs entries exists: ```bash root@webserver-api:/var/log/webserver# ls -l total 0 -rw-r--r-- 1 root root 0 Jun 21 05:54 flask.log root@webserver-api:/var/log/webserver# cd /var/machine-learning/log root@webserver-api:/var/machine-learning/log# ls -l...

We'll need to fix, and ensure that some logging mechanism is capable of capturing errors associated with our [earlier](https://github.com/jeff1evesque/machine-learning/issues/3284#issuecomment-425756516) `500` errors. However, before proceeding, we'll likely need to fix #3287....

This issue should be broken down more strategically, since it's non-trivial. Without proper investigating (more than just #2301), we can only speculate `num_issues = 2 * (num_kernels x num_algorithms x...

@cliffano, what if we just templatize some of the main configurations files as a workaround to a hopeful idea that this module would have parameters we could easily set?

sklearn should have the `logit` functionality builtin.

The following is an equivalent implementation via weka: