explainable-ml

Introduction

This tutorial should go over training a model using MindsDB that predicts whether an email is Spam or not. Example dataset can be found here.

Tutorial summary

The tutorial should follow the below steps :

• Connect mindsb to database
• Train new model
• Desc

Yes

How to use Watcher / WatcherClient over tcp/ip network?

Watcher seems to ZMQ server, and WatcherClient is ZMQ Client, but there is no API/Interface to config server IP address.
Do I need to implement a class that inherits from WatcherClient?

Suggested by Melanie Fernandez Pradier:

“Given a model trained on certain features, is there any way I can include additional features (not used in training) but that I want to monitor in the error analysis?"

This is currently possible by enriching the set of input features to the dashboard after the inference step. However, will need further support on the UI side to clearly mark features t

`import numpy as np
import aspect_based_sentiment_analysis as absa
from aspect_based_sentiment_analysis import alignment
from aspect_based_sentiment_analysis import Example

text = "I love mascara"
aspects = ['mascara']

recognizer = absa.aux_models.BasicPatternRecognizer()
nlp = absa.load(pattern_recognizer=recognizer)
task = nlp(text=text, aspects=aspects)
slack = task.examples

pri

Good day everyone

I am using the output variable of my data (isKilled= yes/no) as a protected variable and “yes” as a priviliged value. But every time I run the code, I just get a few metrics calculated and get the output as shown at the end.

Metric calculation : 2/12 metrics calculated for all models ( 10 NA created )

I used the following code, so could you please suggest where is the