article thumbnail

Identification of Hazardous Areas for Priority Landmine Clearance: AI for Humanitarian Mine Action

ML @ CMU

To validate the proposed system, we simulate different scenarios in which the RELand system could be deployed in mine clearance operations using real data from Colombia. Validation results in Colombia. Each entry is the mean (std) performance on validation folds following the block cross-validation rule.

article thumbnail

7 Tips for Dealing With Small Data

KDnuggets

At my workplace, we produce a lot of functional prototypes for our clients. Because of this, I often need to make Small Data go a long way. In this article, I’ll share 7 tips to improve your results when prototyping with small datasets.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Feature selection by random search in Python

KDnuggets

Feature selection is one of the most important tasks in machine learning. Learn how to use a simple random search in Python to get good results in less time.

Python 305
article thumbnail

Common Machine Learning Obstacles

KDnuggets

In this blog, Seth DeLand of MathWorks discusses two of the most common obstacles relate to choosing the right classification model and eliminating data overfitting.

article thumbnail

Predict football punt and kickoff return yards with fat-tailed distribution using GluonTS

Flipboard

Models were trained and cross-validated on the 2018, 2019, and 2020 seasons and tested on the 2021 season. To avoid leakage during cross-validation, we grouped all plays from the same game into the same fold. For more information on how to use GluonTS SBP, see the following demo notebook.

article thumbnail

How to Make GridSearchCV Work Smarter, Not Harder

Mlearning.ai

Figure 1: Brute Force Search It is a cross-validation technique. Figure 2: K-fold Cross Validation On the one hand, it is quite simple. Running a cross-validation model of k = 10 requires you to run 10 separate models. 2019) Data Science with Python. 2019) Applied Supervised Learning with Python.

article thumbnail

Calibration Techniques in Deep Neural Networks

Heartbeat

Label Smoothing Equation [5] In their 2019 paper “ When does label smoothing help? ”, Hinton et al. [5] logits of the final layer), which helps reduce overconfidence and subsequently reduces the network’s ECE. ” Advances in neural information processing systems 32 (2019). [6] The parameter ɑ controls the degree of smoothing.