Efficient learning algorithm for sparse subsequence pattern-based classification and applications to comparative animal trajectory data analysis.
Takuto SakumaKazuya NishiKaoru KishimotoKazuya NakagawaMasayuki KarasuyamaYuta UmezuShinsuke KajiokaShuhei J. YamazakiKoutarou D. KimuraSakiko MatsumotoKen YodaMatasaburo FukutomiHisashi ShidaraHiroto OgawaIchiro TakeuchiPublished in: Adv. Robotics (2019)
Keyphrases
- data analysis
- learning algorithm
- machine learning
- machine learning algorithms
- classification algorithm
- text classification
- pattern recognition
- pattern matching
- decision trees
- support vector machine
- supervised learning
- feature extraction
- generalization ability
- classification method
- machine learning methods
- classification accuracy
- class labels
- feature selection
- support vector machine svm
- unsupervised learning
- dictionary learning
- feature space
- training data
- nearest neighbour algorithm
- pattern classification
- sparse coding
- automatic classification
- data pre processing
- cross validation
- data mining
- image classification
- feature vectors
- decision rules
- back propagation
- artificial neural networks
- high dimensional
- training set
- learning scheme
- association rules
- sparse data
- trajectory data
- preprocessing
- video sequences