… The example is, like many of the examples in books on data mining and machine learning,
is a classification problem. It comes from a study of geographical variation in plant …

… data collection and pre-processing process, load disaggregation models and algorithms,
data … Finally, some challenges that the current research are confronted with are analyzed and …

… algorithm, a classification prediction model was constructed to train and test the daily transaction
data of … constructed by the xgboost algorithm are higher than other algorithms, and the …

… A comparative study in text categorization. Proceedings of the 14th International Conference
on Machine Learning. San Francisco: Morgan Kaufmann, 1997: 412-442. …

… data of Qingdao city, land cover in the study area was classified and studied by stratified
classification method… First of all, by making the necessary data preprocessing, the spectral …

… mining and then describe the motivation of this research. Afterwards, we present a survey on
the state-of-the-art of opinion mining … , claim extraction and sentiment analysis, followed by …

… and multi-channel sleep data. We compare the classification results of different methods,
and point out that the multi task analyses with deep learning algorithms on multi-channel data …

… ensemble algorithms. Based on the Stacking framework,we build two-layer classification …
The results of the empirical analysis show that, compared with the single machine learning …

… For this purpose, from the investigation of relevant literatures and latest research results, the
characteristics of unsupervised learning algorithms are highlighted. At present, the topology …