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Dynamic Deep Forest: An Ensemble Classification Method for Network Intrusion Detection

Bo Hu, Jinxi Wang, Yifan Zhu, Tan Yang
2019 Electronics  
It uses cascade tree structure to strengthen the representation learning ability.  ...  The proposed Dynamic Deep Forest is a tree-based ensemble approach and consists of two parts. The first part, Multi-Grained Traversing, uses selectors to pick up features as complete as possible.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/electronics8090968 fatcat:d5jhhbrb3ney3ms332rgtv2mu4

An Ensemble Cascading Extremely Randomized Trees Framework for Short-Term Traffic Flow Prediction

2019 KSII Transactions on Internet and Information Systems  
In this paper, we design an ensemble cascading prediction framework based on extremely randomized trees (extra-trees) using a boosting technique called EET to predict the short-term traffic flow under  ...  Extra-trees is a tree-based ensemble method. It essentially consists of strongly randomizing both the attribute and cut-point choices while splitting a tree node.  ...  Contributions In this paper, we propose an ensemble cascading prediction framework based on extremely randomized trees (extra-trees) and a boosting technique with high prediction accuracy and low computational  ... 
doi:10.3837/tiis.2019.04.013 fatcat:7smgp7wkhze6fk6sidmjkh23be

Comparison of parallel algorithms for path expression query in object database systems

Guoren Wang, Ge Yu, K. Kaneko, A. Makinouchi
2001 Proceedings Seventh International Conference on Database Systems for Advanced Applications DASFAA 2001 DASFAA-01  
Moreover. a iiew sclieduliiig strategy called right-deep zigzag tree is designed to further improve the performance of the PCSJ algorithm.  ...  ~~z~)) wheii ctmiputing path expressions with restrictive predicates and that tlie right-deep zigzag tree scheduling strategy has tlie better performance than the right-deep tree sclieduliiig strategy.  ...  So, riglit-deep zigzag tree car1 also be iiarricd cascade seginciited riglit-deep tree, to reflect tlie cascade feature of patli exprcssioris. 111 this subscctioii, we will discuss the parallel executioii  ... 
doi:10.1109/dasfaa.2001.916385 dblp:conf/dasfaa/WangYKM01 fatcat:ygi3ziek3fdmfnp5plkckyje7u

Disease Classification within Dermascopic Images Using features extracted by ResNet50 and classification through Deep Forest [article]

Suhita Ray
2018 arXiv   pre-print
Instead, we use Deep Forest, a novel decision tree ensemble approach with performance highly competitive to deep neural networks in a broad range of tasks.  ...  Also as the Deep Forest network decides its complexity by itself, it also caters to the problem of dataset imbalance we faced in this problem.  ...  However due to paucity of time we could not explore this region. We leave this as a future scope of improvement.  ... 
arXiv:1807.05711v3 fatcat:pv22eb7xgnbnzbochrdk7gryki

Comparing Boosted Cascades to Deep Learning Architectures for Fast and Robust Coconut Tree Detection in Aerial Images

Steven Puttemans, Kristof Van Beeck, Toon Goedemé
2018 Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications  
the task of fast and robust coconut tree detection and classification in aerial imagery.  ...  Object detection using a boosted cascade of weak classifiers is a principle that has been used in a variety of applications, ranging from pedestrian detection to fruit counting in orchards, and this with  ...  CONCLUSIONS With this research we have proven both the capabilities of boosted cascade as well as deep learned detection models for coconut tree localisation in aerial images.  ... 
doi:10.5220/0006571902300241 dblp:conf/visapp/PuttemansBG18 fatcat:qclu4zi4sfbanmvom3pqypujqq

Deep forest regression for short-term load forecasting of power systems

Linfei Yin, Zhixiang Sun, Fang Gao, Hui Liu
2020 IEEE Access  
Deep forest regression includes two procedures, i.e., multi-grained scanning procedure and cascade forest procedure.  ...  INDEX TERMS Deep forest regression, short-term load forecasting, multi-grained scanning procedure, cascade forest procedure.  ...  The number of cascade forests is equal to the depth of the deep forest model. The number of cascade forests of deep forest is determined automatically by the training process of the deep forest.  ... 
doi:10.1109/access.2020.2979686 fatcat:2beatb6psvd4rgia5q6egjavnq

Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud [article]

Ya-Lin Zhang, Jun Zhou, Wenhao Zheng, Ji Feng, Longfei Li, Ziqi Liu, Ming Li, Zhiqiang Zhang, Chaochao Chen, Xiaolong Li, Zhi-Hua Zhou, YUAN QI
2020 arXiv   pre-print
We tested the deep forest model on an extra-large scale task, i.e., automatic detection of cash-out fraud, with more than 100 millions of training samples.  ...  the cascade level.  ...  This research was partially supported by the National Key R&D Program of China (2018YFB1004300), the National Science Foundation of China (61751306), and the Collaborative Innovation Center of Novel Software  ... 
arXiv:1805.04234v3 fatcat:iwrny7pogvcezfz6ukvjcg35tu

Fast Pedestrian Detection With Attention-Enhanced Multi-Scale RPN and Soft-Cascaded Decision Trees

Han Wang, Yali Li, Shengjin Wang
2019 IEEE transactions on intelligent transportation systems (Print)  
Inspired by the success of traditional pedestrian detectors, we use soft-cascaded decision trees instead of cascaded deep neural networks to achieve high accuracy and fast detection speed simultaneously  ...  The decision tree classifier is used and enables us to combine features from different layers with various resolutions for classification and incorporate effective bootstrapping for mining hard negatives  ...  Features Decision tree classifier is flexible and has no need of feature normalization, so the features for classification can be drawn from an arbitrary combination of convolution layers with no extra  ... 
doi:10.1109/tits.2019.2948398 fatcat:l4lyqfsxe5bf3d6fis5s6txrh4

Time-Complexity of Multilayered DNA Strand Displacement Circuits [chapter]

Georg Seelig, David Soloveichik
2009 Lecture Notes in Computer Science  
The potential applications of this and similar technologies inspire the study of the computation time of multilayered molecular circuits.  ...  Our results rely on simple asymptotic arguments that should be applicable to a wide class of chemical circuits.  ...  Ho-Lin Chen suggested how to optimize lemma 1 to be within a factor of 4 of the upper bound of lemma 2.  ... 
doi:10.1007/978-3-642-10604-0_15 fatcat:bnyayrgh7zdyxaqhu6rqdarcky

Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System [article]

Hong Wen, Jing Zhang, Quan Lin, Keping Yang, Pipei Huang
2018 arXiv   pre-print
In this paper, we tackle this problem by proposing multi-Level Deep Cascade Trees (ldcTree), which is a novel decision tree ensemble approach.  ...  It leverages deep cascade structures by stacking Gradient Boosting Decision Trees (GBDT) to effectively learn feature representation.  ...  Acknowledgment This work was partly supported by the National Natural Science Foundation of China (NSFC) under Grants 61806062 and 61751304.  ... 
arXiv:1805.09484v3 fatcat:pdfadn7zlnbipfn4nbkvsx26mq

A Cascade Deep Forest Model for Breast Cancer Subtype Classification Using Multi-Omics Data

Ala'a El-Nabawy, Nahla A. Belal, Nashwa El-Bendary
2021 Mathematics  
conventional deep neural networks (DNNs), especially for imbalanced training sets, through learning hyper-representations through using cascade ensemble decision trees.  ...  The significance of this work is that it is shown that using gene expression data alone with the cascade Deep Forest classifier achieves comparable accuracy to other techniques with higher computational  ...  The cascade Deep Forest model fully uses the characteristics of both deep neural networks and ensemble models.  ... 
doi:10.3390/math9131574 fatcat:4b5perv7ifaqpcbnpqyqau4sga

Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System

Hong Wen, Jing Zhang, Quan Lin, Keping Yang, Pipei Huang
2019 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
In this paper, we tackle this problem by proposing multiLevel Deep Cascade Trees (ldcTree), which is a novel decision tree ensemble approach.  ...  It leverages deep cascade structures by stacking Gradient Boosting Decision Trees (GBDT) to effectively learn feature representation.  ...  Acknowledgment This work was partly supported by the National Natural Science Foundation of China (NSFC) under Grants 61806062 and 61751304.  ... 
doi:10.1609/aaai.v33i01.3301338 fatcat:qpua5ij7ybdatdfdwpsviecjmm

Prediction of protein-protein interactions based on elastic net and deep forest [article]

Bin Yu, Cheng Chen, Zhaomin Yu, Anjun Ma, Bingqiang Liu, Qin Ma
2020 bioRxiv   pre-print
We present a novel deep-forest-based method for PPIs prediction.  ...  Finally, GcForest-PPI model based on deep forest is built up. Benchmark experiments reveal that the accuracy values of Saccharomyces cerevisiae and Helicobacter pylori are 95.44% and 89.26%.  ...  Then ensemble XGBoost, 320 RF and Extra-Trees via cascade architecture to implement the task, and the predictive tool 321 GcForest-PPI for PPIs based on deep forest is built up. 322 Step 5: Model evaluation  ... 
doi:10.1101/2020.04.23.058644 fatcat:p6aolklvj5bofjqgylsuw2zjom

Cascaded deep monocular 3D human pose estimation with evolutionary training data [article]

Shichao Li, Lei Ke, Kevin Pratama, Yu-Wing Tai, Chi-Keung Tang, Kwang-Ting Cheng
2021 arXiv   pre-print
End-to-end deep representation learning has achieved remarkable accuracy for monocular 3D human pose estimation, yet these models may fail for unseen poses with limited and fixed training data.  ...  Extensive experiments show that our approach not only achieves state-of-the-art accuracy on the largest public benchmark, but also generalizes significantly better to unseen and rare poses.  ...  extra data.  ... 
arXiv:2006.07778v2 fatcat:tnx2fvcn3zcpvlbj27pyaq7ola

Page 3 of Home Progress Vol. 3, Issue 10 [page]

1914 Home Progress  
The subjects ’ range from wild apples to the big trees, from fair gardens to the*wildest scenery, and from ocean to ocean.’? — Philadelphia North American. Illustrated. $1.50 met. Postage extra.  ...  The Spell of the Rockies “To read this book is to climb with the author almost inaccessible heights, to know the spirit of deep forests, to be initiated into much secret lore of mountain, meadow and wood  ... 
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