[[1] BLUM, Avrim L., LANGLEY, Pat. 1997. Selection of relevant features and examples in machine learning. Artificial intelligence, 97.1-2: 245-271.10.1016/S0004-3702(97)00063-5]Search in Google Scholar
[[2] LANGLEY, Pat. 1994. Selection of relevant features in machine learning. In: Proceedings of the AAAI Fall symposium on relevance, pp. 1-5.10.21236/ADA292575]Search in Google Scholar
[[3] BONTEMPI, Gianluca, TAIEB, Souhaib Ben, LE BORGNE, Yann-Aël. 2012. Machine learning strategies for time series forecasting. In: European business intelligence summer school. Springer, Berlin, Heidelberg, pp. 62-77.10.1007/978-3-642-36318-4_3]Search in Google Scholar
[[4] MITCHELL, Tom M. 1999. Machine learning and data mining. Communications of the ACM, 42.11.10.1145/319382.319388]Search in Google Scholar
[[5] FAWCETT, Tom; PROVOST, Foster J. 1996. Combining Data Mining and Machine Learning for Effective User Profiling. In: KDD, pp. 8-13.]Search in Google Scholar
[[6] MITCHELL, Tom M. 1997. Does machine learning really work? AI magazine, 18.3: 11-11.]Search in Google Scholar
[[7] KOSTELICH, Eric J., SCHREIBER, Thomas. 1993. Noise reduction in chaotic time-series data: A survey of common methods. Physical Review E, 48.3: 1752.10.1103/PhysRevE.48.1752]Search in Google Scholar
[[8] BAR-JOSEPH, Ziv. 2004. Analyzing time series gene expression data. Bioinformatics, 20.16: 2493-2503.10.1093/bioinformatics/bth283]Search in Google Scholar