I’m working on a machine learning project, and my dataset contains variables about social, demographic and economic aspects of 218 countries, ranging from 1960 to 2022. The target variable is a binary variable (Yes or No) that represents if the country has had at least one attempt of coup d’etat in a specific year.
My question is: what are the best classification models for multi-level..
Tag : machine-learning
Improving the four basic language skills “Listening”, “Speaking”, “Reading” and “Writing” Th..
I have two class of data. I want to separate their features that is strong wind and weak wind and I have two variables and a specific threshold that can be used to separate the features but I want to train a model and want that if the data changes with time, the threshold for wind to separate also should adapt accordingly.
Can anyone suggest on this which machine learning model should be more focused and how the dynamic threshold can be pre..
I have this code where I don’t understand where the error is when I calculate the cross_val_score.
You can find the code at the end.
When I insert X and Y into cross_val_score I get this output= [-1.04310278e+25 -9.02663688e-01 -5.58849445e-01 -4.67666181e-01
-5.31695826e-01 -5.38521348e-01 -4.88145909e-01 -9.43066823e-01
-8.05226210e-01 -1.0890764..
I’ve been trying to make a code snippet prediction model to predict/complete the next set of code. Something sort of the copilot has in the text box but for code which i will use it to deploy it on a website. What model should i use.Copilot te..
Closed 45 secs ago
I’m using the MAPIE Python library for conformal predictions. In the MapieClassifier I choose method='score'. When alpha is small (between 1% and 5%) I get non empty prediction sets. However when I look at a full range of alphas from 1% to 99% (e.g. alphas = np.arange(0.01,1.00,0.01)) the average number of classes in the prediction sets gradually go down to zero, despite the fact that in C. Molnar’s book Introduction To Conformal Prediction With Python (2023) p.27 it is stated that « A prediction set – for multi-class tasks – is a set of one or more classes. », i.e. it’s a non empty subset of the set of target modalities. I used a default XGBoost model on two classification datasets and got this phenomenon of empty prediction sets with big alphas, one of which was the Dry Bean dataset mentioned in Molnar’s..
I looked at using python for the AI in a security application for hobby-business but apparently you either release it as source code or it can be easily decompiled. Of the new machine learning languages/packages, which can be kept confiden..