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SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting
Threshold Autoregressive (TAR) models have been widely used by statisticians for non-linear time series forecasting during the past few decades, due...
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Decision Tree Clustering for Time Series Data: An Approach for Enhanced Interpretability and Efficiency
Clustering is one of the unsupervised learning methods for grou** similar data samples. While clustering has been used in a wide range, traditional...
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Overcoming Weak Scaling Challenges in Tree-Based Nearest Neighbor Time Series Mining
The mining of time series data plays an important role in modern information retrieval and monitoring infrastructures. In particular, the...
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Huffman Tree Based Multi-resolution Temporal Convolution Network for Electricity Time Series Prediction
Electricity time series prediction is a fundamental part in electricity system scheduling that maintains the balance between electrical supply and...
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Decision Tree
This chapter first introduces the basic concept of the decision tree, then introduces feature selection, tree-generation and tree-pruning through ID3...
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Time Series
There is a very old story about time series analysis. In ancient Egypt 7000 years ago, people recorded the ups and downs of the Nile River day by day...
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NBD-Tree: Neural Bounded Deformation Tree for Collision Culling of Deformable Objects
We propose a novel machine learning-based approach for accelerating the broad phase of 3D collision detection for deformable objects. Our method,...
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Weighted Tree Automata with Constraints
The HOM problem, which asks whether the image of a regular tree language under a given tree homomorphism is again regular, is known to be decidable...
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Unsupervised feature based algorithms for time series extrinsic regression
Time Series Extrinsic Regression (TSER) involves using a set of training time series to form a predictive model of a continuous response variable...
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Tree-Walking-Storage Automata
We introduce and investigate tree-walking-storage automata, which are finite-state devices equipped with a tree-like storage. The automata are...
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Forecasting PM2.5 Concentration Using Gradient-Boosted Regression Tree with CNN Learning Model
AbstractAir pollution imposed by particle matter (PM) made it a public health concern and hazard to humans and the environment. Reduced vision,...
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Recursive tree grammar autoencoders
Machine learning on trees has been mostly focused on trees as input. Much less research has investigated trees as output, which has many...
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Children age group detection based on human–computer interaction and time series analysis
This article proposes a novel children–computer interaction (CCI) approach for the task of age group detection. This approach focuses on the...
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Up Sampling Data in Bagging Tree Classification and Regression Decision Tree Method for Dengue Shock Syndrome Detection
Dengue virus, DENV, is the cause of dengue fever and carries the risk of develo** dengue hemorrhagic fever and dengue shock syndrome (DSS), which...
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Scalable Tree-based Register Automata Learning
Existing active automata learning (AAL) algorithms have demonstrated their potential in capturing the behavior of complex systems (e.g., in analyzing...
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Clock Tree
Until this point, there’s been an elephant in the room. We’ve configured and used various clocks without saying too much about them. Now is a good...
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Best-tree wavelet packet transform bidirectional GRU for short-term load forecasting
This work proposes the short-term load forecasting (STLF) using a combination of wavelet transform (WT) and bidirectional gated recurrent unit...
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Fully Dynamic Algorithms for Euclidean Steiner Tree
The Euclidean Steiner tree problem asks to find a min-cost metric graph that connects a given set of terminal points X in...
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Network Design on Undirected Series-Parallel Graphs
We study the single pair capacitated network design problem and the budget constrained max flow problem on undirected series-parallel graphs. These...
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CAT: a coarse-to-fine attention tree for semantic change detection
Semantic change detection (SCD) and land cover map** (LCM) are always treated as a dual task in the field of remote sensing. However, due to...
