Image Created by Author. Without a penalty, the line of best fit has a steeper slope, which means that it is more sensitive to small changes in X. By introducing a penalty, the line of best fit becomes less sensitive to small changes in X. This is the idea behind ridge regression. La...
Methods: Hyperpolarized 3He MRI was acquired using a coronal Cartesian FGRE sequence with a partial echo and segmented using a k-means cluster algorithm. A maximum entropy mask was used to generate a region of interest for texture feature extraction using a custom-built algorithm and PyRadiomics ...
The algorithm isn't simply returning the values that account for the biggest amount of the change. For example, if most (98%) sales came from the USA, then it would commonly be the case that most of the increase was also in the USA. Yet unless the USA or other countries/regions had...
While SHAP can explain the output of any machine learning model, we have developed a high-speed exact algorithm for tree ensemble methods (see our Nature MI paper). Fast C++ implementations are supported for XGBoost, LightGBM, CatBoost, scikit-learn and pyspark tree models: import xgboost import...
We build risk classes according to each region’s risk of exposure to COVID-19 cases by performing a 1-dimensional k-means38 unsupervised clustering algorithm on the number of cases for each wave, with a varying number of clusters: we found that two clusters is an optimal choice, in terms...
In order to examine how well the exploratory high-capacity model corresponded to a reward-oriented behaviour, i.e., actions that endeavour to maximise the acquired reward, we fitted a reinforcement learning model to the data using a q-learning algorithm15. This model assumes that participants mak...
How many clusters can the K-Means algorithm differentiate between? Find the following value of t. t_{0.5, 143} True or false? Exponential smoothing is a weighted averaging method that is still relatively easy to use and understand. Explain whether 'math courses taken' is normally distributed?
Discuss the pros and cons of k-means clustering compared to hierarchical clustering. What is the difference between classification and regression? What is a classification algorithm? What is unsupervised classification? What is rule-based classification?
The agents have their own optical coherence tomography (OCT) images on which they apply a distinct machine learning algorithm. The learned model is used to extract diagnosis rules. With distinct learned rules, the agents engage in an argumentative process. The resolution of the debate outputs a ...
To further ensure that our method works fast, R package treeshap integrates C++ implementation of the algorithm. TreeSHAP was originally implemented as a part of Python package shap (link to the GitHub). In the past, as MI2DataLab we have developed an R wrapper of this library — ...