Performance Analysis of Support Vector Machine (SVM) on Challenging Datasets for Forest Fire Detection
Fuente:
arXiv
Saved in:
| Main Authors: | Kar, Ankan, Nath, Nirjhar, Kemprai, Utpalraj, Aman |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Sparse Learning and Class Probability Estimation with Weighted Support Vector Machines
by: Zeng, Liyun, et al.
Published: (2023)
by: Zeng, Liyun, et al.
Published: (2023)
Elite-Driven Support Vector Machines for Classification
by: Jozani, Mohammad Jafari, et al.
Published: (2026)
by: Jozani, Mohammad Jafari, et al.
Published: (2026)
A Large-Scale Empirical Comparison of Meta-Learners and Causal Forests for Heterogeneous Treatment Effect Estimation in Marketing Uplift Modeling
by: Singh, Aman
Published: (2026)
by: Singh, Aman
Published: (2026)
Horseshoe Forests for High-Dimensional Causal Survival Analysis
by: Jacobs, Tijn, et al.
Published: (2025)
by: Jacobs, Tijn, et al.
Published: (2025)
Identifying Peer Influence in Therapeutic Communities Adjusting for Latent Homophily
by: Nath, Shanjukta, et al.
Published: (2022)
by: Nath, Shanjukta, et al.
Published: (2022)
Interpretable Machine Learning for Survival Analysis
by: Langbein, Sophie Hanna, et al.
Published: (2024)
by: Langbein, Sophie Hanna, et al.
Published: (2024)
Vector Quantile Regression on Manifolds
by: Pegoraro, Marco, et al.
Published: (2023)
by: Pegoraro, Marco, et al.
Published: (2023)
Ordinal Mixed-Effects Random Forest
by: Bergonzoli, Giulia, et al.
Published: (2024)
by: Bergonzoli, Giulia, et al.
Published: (2024)
Global Censored Quantile Random Forest
by: Zhou, Siyu, et al.
Published: (2024)
by: Zhou, Siyu, et al.
Published: (2024)
Extended Isolation Forest with feature sensitivities
by: Donhauzer, Illia
Published: (2026)
by: Donhauzer, Illia
Published: (2026)
Interpretable Network-assisted Random Forest+
by: Tang, Tiffany M., et al.
Published: (2025)
by: Tang, Tiffany M., et al.
Published: (2025)
Principal Component Analysis When n < p: Challenges and Solutions
by: Weeraratne, Nuwan, et al.
Published: (2025)
by: Weeraratne, Nuwan, et al.
Published: (2025)
Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis
by: Ham, Dae Woong, et al.
Published: (2022)
by: Ham, Dae Woong, et al.
Published: (2022)
MMD-based Variable Importance for Distributional Random Forest
by: Bénard, Clément, et al.
Published: (2023)
by: Bénard, Clément, et al.
Published: (2023)
Generalized Random Forests using Fixed-Point Trees
by: Fleischer, David, et al.
Published: (2023)
by: Fleischer, David, et al.
Published: (2023)
missForestPredict -- Missing data imputation for prediction settings
by: Albu, Elena, et al.
Published: (2024)
by: Albu, Elena, et al.
Published: (2024)
On Quantile Regression Forests for Modelling Mixed-Frequency and Longitudinal Data
by: Andreani, Mila
Published: (2025)
by: Andreani, Mila
Published: (2025)
Generative Conformal Prediction with Vectorized Non-Conformity Scores
by: Zheng, Minxing, et al.
Published: (2024)
by: Zheng, Minxing, et al.
Published: (2024)
Enhancing Airline Customer Satisfaction: A Machine Learning and Causal Analysis Approach
by: Mirthipati, Tejas
Published: (2024)
by: Mirthipati, Tejas
Published: (2024)
Depth Functions for Partial Orders with a Descriptive Analysis of Machine Learning Algorithms
by: Blocher, Hannah, et al.
Published: (2023)
by: Blocher, Hannah, et al.
Published: (2023)
What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work?
by: Dandl, Susanne, et al.
Published: (2022)
by: Dandl, Susanne, et al.
Published: (2022)
Forests for Differences: Robust Causal Inference Beyond Parametric DiD
by: Souto, Hugo Gobato, et al.
Published: (2025)
by: Souto, Hugo Gobato, et al.
Published: (2025)
Order Selection in Vector Autoregression by Mean Square Information Criterion
by: Hellstern, Michael, et al.
Published: (2025)
by: Hellstern, Michael, et al.
Published: (2025)
Provable Recovery of Locally Important Signed Features and Interactions from Random Forest
by: Vuk, Kata, et al.
Published: (2025)
by: Vuk, Kata, et al.
Published: (2025)
Distributional Random Forests for Complex Survey Designs on Reproducing Kernel Hilbert Spaces
by: Zou, Yating, et al.
Published: (2025)
by: Zou, Yating, et al.
Published: (2025)
Combining SHAP and Causal Analysis for Interpretable Fault Detection in Industrial Processes
by: Santos, Pedro Cortes dos, et al.
Published: (2025)
by: Santos, Pedro Cortes dos, et al.
Published: (2025)
An Interpretable and Efficient Infinite-Order Vector Autoregressive Model for High-Dimensional Time Series
by: Zheng, Yao
Published: (2022)
by: Zheng, Yao
Published: (2022)
The Missing Link: Allocation Performance in Causal Machine Learning
by: Fischer-Abaigar, Unai, et al.
Published: (2024)
by: Fischer-Abaigar, Unai, et al.
Published: (2024)
Vector-Valued Distributional Reinforcement Learning Policy Evaluation: A Hilbert Space Embedding Approach
by: Mohammadi, Mehrdad, et al.
Published: (2026)
by: Mohammadi, Mehrdad, et al.
Published: (2026)
Causal Decomposition Analysis with Synergistic Interventions: A Triply-Robust Machine Learning Approach to Addressing Multiple Dimensions of Social Disparities
by: Park, Soojin, et al.
Published: (2025)
by: Park, Soojin, et al.
Published: (2025)
RFX: High-Performance Random Forests with GPU Acceleration and QLORA Compression
by: Kuchar, Chris
Published: (2025)
by: Kuchar, Chris
Published: (2025)
Vector Copula Variational Inference and Dependent Block Posterior Approximations
by: Fu, Yu, et al.
Published: (2025)
by: Fu, Yu, et al.
Published: (2025)
Maximum Risk Minimization with Random Forests
by: Freni, Francesco, et al.
Published: (2025)
by: Freni, Francesco, et al.
Published: (2025)
Challenges in Variable Importance Ranking Under Correlation
by: Liang, Annie, et al.
Published: (2024)
by: Liang, Annie, et al.
Published: (2024)
A Look into How Machine Learning is Reshaping Engineering Models: the Rise of Analysis Paralysis, Optimal yet Infeasible Solutions, and the Inevitable Rashomon Paradox
by: Naser, MZ
Published: (2025)
by: Naser, MZ
Published: (2025)
Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery
by: Wang, Caixing, et al.
Published: (2024)
by: Wang, Caixing, et al.
Published: (2024)
Recursive Equations For Imputation Of Missing Not At Random Data With Sparse Pattern Support
by: Phung, Trung, et al.
Published: (2025)
by: Phung, Trung, et al.
Published: (2025)
meval: A Statistical Toolbox for Fine-Grained Model Performance Analysis
by: Sutariya, Dishantkumar, et al.
Published: (2025)
by: Sutariya, Dishantkumar, et al.
Published: (2025)
The Challenges of Hyperparameter Tuning for Accurate Causal Effect Estimation
by: Machlanski, Damian, et al.
Published: (2023)
by: Machlanski, Damian, et al.
Published: (2023)
Invariant Causal Set Covering Machines
by: Godon, Thibaud, et al.
Published: (2023)
by: Godon, Thibaud, et al.
Published: (2023)
Similar Items
-
Sparse Learning and Class Probability Estimation with Weighted Support Vector Machines
by: Zeng, Liyun, et al.
Published: (2023) -
Elite-Driven Support Vector Machines for Classification
by: Jozani, Mohammad Jafari, et al.
Published: (2026) -
A Large-Scale Empirical Comparison of Meta-Learners and Causal Forests for Heterogeneous Treatment Effect Estimation in Marketing Uplift Modeling
by: Singh, Aman
Published: (2026) -
Horseshoe Forests for High-Dimensional Causal Survival Analysis
by: Jacobs, Tijn, et al.
Published: (2025) -
Identifying Peer Influence in Therapeutic Communities Adjusting for Latent Homophily
by: Nath, Shanjukta, et al.
Published: (2022)