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Tag: tree

  • Modern Git-aware File Tree and global search/replace in Jupyter

    Modern Git-aware File Tree and global search/replace in Jupyter I used jupyter lab for years, but the file browser menu is lack of some important features like tree view/aware of git status; I tried some of the old 3rd extensions but none of them fit those modern demands which most of editors/IDE have(like vscode) so…

  • The Machine Learning “Advent Calendar” Day 7: Decision Tree Classifier

    The Machine Learning “Advent Calendar” Day 7: Decision Tree Classifier In Day 6, we saw how a Decision Tree Regressor finds its optimal split by minimizing the Mean Squared Error. Today, for Day 7 of the Machine Learning “Advent Calendar”, we switch to classification. With just one numerical feature and two classes, we explore how…

  • The Machine Learning “Advent Calendar” Day 6: Decision Tree Regressor

    The Machine Learning “Advent Calendar” Day 6: Decision Tree Regressor During the first days of this Machine Learning Advent Calendar, we explored models based on distances. Today, we switch to a completely different way of learning: Decision Trees. With a simple one-feature dataset, we can see how a tree chooses its first split. The idea…

  • An RKHS Perspective on Tree Ensembles

    An RKHS Perspective on Tree Ensembles arXiv:2512.00397v1 Announce Type: new Abstract: Random Forests and Gradient Boosting are among the most effective algorithms for supervised learning on tabular data. Both belong to the class of tree-based ensemble methods, where predictions are obtained by aggregating many randomized regression trees. In this paper, we develop a theoretical framework…

  • The Tree-SNE Tree Exists

    The Tree-SNE Tree Exists arXiv:2510.15014v1 Announce Type: new Abstract: The clustering and visualisation of high-dimensional data is a ubiquitous task in modern data science. Popular techniques include nonlinear dimensionality reduction methods like t-SNE or UMAP. These methods face the `scale-problem’ of clustering: when dealing with the MNIST dataset, do we want to distinguish different digits…

  • Next-Depth Lookahead Tree

    Next-Depth Lookahead Tree arXiv:2509.15143v1 Announce Type: new Abstract: This paper proposes the Next-Depth Lookahead Tree (NDLT), a single-tree model designed to improve performance by evaluating node splits not only at the node being optimized but also by evaluating the quality of the next depth level. Jaeho Lee, Kangjin Kim, Gyeong Taek Lee Go to original…

  • Tree of Thought Prompting: Teaching LLMs to Think Slowly

    Tree of Thought Prompting: Teaching LLMs to Think Slowly Playing Minesweeper with Augmented Reasoning The post Tree of Thought Prompting: Teaching LLMs to Think Slowly appeared first on Towards Data Science. Shuyang Go to original source

  • PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders

    PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders arXiv:2502.04730v1 Announce Type: new Abstract: Learning informative representations of phylogenetic tree structures is essential for analyzing evolutionary relationships. Classical distance-based methods have been widely used to project phylogenetic trees into Euclidean space, but they are often sensitive to the choice of distance metric and may lack…