72 citations · 760 across the 54 of their papers we have counts for
11 papers · 1 filter
Fast likelihood-based change point detection
Nikolaj Tatti
Change point detection plays a fundamental role in many real-world applications, where the goal is to analyze and monitor the behaviour of a data stream. In this paper, we study ch…
Approximation algorithms for confidence bands for time series
Nikolaj Tatti
Confidence intervals are a standard technique for analyzing data. When applied to time series, confidence intervals are computed for each time point separately. Alternatively, we c…
Maintaining AUC and -measure over time
Nikolaj Tatti
Measuring the performance of a classifier is a vital task in machine learning. The running time of an algorithm that computes the measure plays a very small role in an offline sett…
Decomposable Families of Itemsets
Nikolaj Tatti, Hannes Heikinheimo
The problem of selecting a small, yet high quality subset of patterns from a larger collection of itemsets has recently attracted lot of research. Here we discuss an approach to th…
Tell Me Something I Don't Know: Randomization Strategies for Iterative Data Mining
Sami Hanhijärvi, Markus Ojala, Niko Vuokko +3
There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for the same dataset. This, however,…
Maximum Entropy Based Significance of Itemsets
Nikolaj Tatti
We consider the problem of defining the significance of an itemset. We say that the itemset is significant if we are surprised by its frequency when compared to the frequencies of…
Discovering Episodes with Compact Minimal Windows
Nikolaj Tatti
Discovering the most interesting patterns is the key problem in the field of pattern mining. While ranking or selecting patterns is well-studied for itemsets it is surprisingly und…
Using Background Knowledge to Rank Itemsets
Nikolaj Tatti, Michael Mampaey
Assessing the quality of discovered results is an important open problem in data mining. Such assessment is particularly vital when mining itemsets, since commonly many of the disc…
What is the dimension of your binary data?
Nikolaj Tatti, Taneli Mielikainen, Aristides Gionis +1
Many 0/1 datasets have a very large number of variables; on the other hand, they are sparse and the dependency structure of the variables is simpler than the number of variables wo…
Efficient estimation of AUC in a sliding window
Nikolaj Tatti
In many applications, monitoring area under the ROC curve (AUC) in a sliding window over a data stream is a natural way of detecting changes in the system. The drawback is that com…
A note on adjusting for using with cross-validation
Indre Zliobaite, Nikolaj Tatti
We show how to adjust the coefficient of determination () when used for measuring predictive accuracy via leave-one-out cross-validation.