An efficient algorithm for sequential random sampling
نویسندگان
چکیده
منابع مشابه
An Efficient Sampling Algorithm for Influence Diagrams
We describe an efficient sampling algorithm for solving influence diagrams that achieves its efficiency by reusing samples for each of the decision strategies. Our algorithm is exhaustive in the sense of computing the expected utility of each of the possible decision strategies. We show how by a parallel evaluation of all strategies we not only save a significant amount of computation but also ...
متن کاملCMRULES: An Efficient Algorithm for Mining Sequential Rules Sequential Rules
We propose CMRULES, an algorithm for mining sequential rules common to many sequences in sequence databases not for mining rules appearing frequently in sequences. For this reason, the algorithm does not use a sliding window approach. Instead, it first finds association rules to prune the search space for items that occur jointly in many sequences. Then it eliminates association rules that do n...
متن کاملAn Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering
We propose an efficient sequential Monte Carlo inference scheme for the recently proposed coalescent clustering model [1]. Our algorithm has a quadratic runtime while those in [1] is cubic. In experiments, we were surprised to find that in addition to being more efficient, it is also a better sequential Monte Carlo sampler than the best in [1], when measured in terms of variance of estimated li...
متن کاملAn Efficient Algorithm for Mining Sequential Rules with Interestingness Measures
Mining sequential rules are an important problem in data mining research. It is commonly used for market decisions, management and behaviour analysis. In traditional association-rule mining, rule interestingness measures such as confidence are used for determining relevant knowledge. They can reduce the size of the search space and select useful or interesting rules from the set of the discover...
متن کاملAn Efficient GA-Based Algorithm for Mining Negative Sequential Patterns
Negative sequential pattern mining has attracted increasing concerns in recent data mining research because it considers negative relationships between itemsets, which are ignored by positive sequential pattern mining. However, the search space for mining negative patterns is much bigger than that for positive ones. When the support threshold is low, in particular, there will be huge amounts of...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ACM Transactions on Mathematical Software
سال: 1987
ISSN: 0098-3500,1557-7295
DOI: 10.1145/23002.23003