AncesTrees: ancestry estimation with randomized decision trees
نویسندگان
چکیده
منابع مشابه
Randomized Boolean Decision Trees: Several Remarks
Assume we want to show that (a) the cost of any randomized decision tree computing a given Boolean function is at least c. To this end it suuces to prove that (b) there is a probability distribution over the set of all assignments to variables of that function with respect to which the average cost of any deterministic decision tree computing that function is at least c. Yao in 11] showed that ...
متن کاملSpeech recognition using randomized relational decision trees
We explore the possibility of recognizing speech signals using a large collection of coarse acoustic events, which describe temporal relations between a small number of local features of the spectrogram. The major issue of invariance to changes in duration of speech signal events is addressed by defining temporal relations in a rather coarse manner, allowing for a large degree of slack. The app...
متن کاملDecision Forests with Oblique Decision Trees
Ensemble learning schemes have shown impressive increases in prediction accuracy over single model schemes. We introduce a new decision forest learning scheme, whose base learners are Minimum Message Length (MML) oblique decision trees. Unlike other tree inference algorithms,MMLoblique decision tree learning does not over-grow the inferred trees. The resultant trees thus tend to be shallow and ...
متن کاملOC1: A randomized algorithm for building oblique decision trees
This paper introduces OC1, a new algorithm for generating multivariate decision trees. Multivariate trees classify examples by testing linear combinations of the features at each non-leaf node of the tree. Each test is equivalent to a hyperplane at an oblique orientation to the axes. Because of the computational intractability of nd-ing an optimal orientation for these hyperplanes, heuristic me...
متن کاملOC1: A Randomized Induction of Oblique Decision Trees
This paper introduces OC1, a new algorithm for generating multivariate decision trees. Multivari-ate trees classify examples by testing linear combinations of the features at each non-leaf node of the tree. Each test is equivalent to a hyperplane at an oblique orientation to the axes. Because of the computational intractability of nding an optimal orientation for these hyperplanes, heuristic me...
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: International Journal of Legal Medicine
سال: 2014
ISSN: 0937-9827,1437-1596
DOI: 10.1007/s00414-014-1050-9