To improve the deduplication performance while keep a reasonable metadata cost and time cost at the same time, a state deduplication method based on variable-size sliding window and a universal model of performance-analyzing for the deduplication methods are proposed. According to this method, the ...
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(2009) Gains in power for exhaustive analyses of haplotypes using variable-sized sliding window strategy: A comparison of association-mapping strategies. Eur J Hum Genet 17:785–792. View ArticleGuo Y, Li J, Bonham AJ, Wang Y, Deng H: Gains in power for exhaustive analyses of haplotypes ...
3、window的生命周期 二、window的分类 1、Tumbling Windows 2、Sliding Windows 3、Session Windows 4、Global Windows 5、按照时间time和数量count分类 6、按照滑动间隔slide和窗口大小size分类 三、窗口函数 1、ReduceFunction 2、AggregateFunction 3、ProcessWindowFunction ...
They keep increasing the size of the window iteratively until the probability density function reached its highest value. Another work by Deypir et al. [36] use variable size sliding window to mine frequent itemsets. They start with an initial window size which is set by luser and then the ...
We consider the problem of maintaining ε-approximate counts and quantiles over a stream sliding window using limited space. We consider two types of sliding windows depending on whether the number of elements N in the window is fixed (fixed-size sliding window) or variable (variable-size ...
To ascertain which variable(s) exert the greatest impact on the estimation of drop width, we carried out a feature importance analysis for the LSTM model with sliding window size of 20 frames. Thus, we utilized the gradient-based feature importance. The feature importance analysis reveals that ...
A variable size sliding window based frequent itemsets mining algorithm in data stream Due to the unpredictability and the concept drift character of the data stream, the traditional sliding window is difficult to adapt to frequent itemsets m... H Li,L Wang - International Conference on Materials...
Computes grouped sliding windows on a 1D array with variable group sizes. Parameters: arr (np.ndarray): Input 1D array. sections (np.ndarray): Indices marking the change to new groups. window (int): Size of the sliding window. step (int, optional): Step size between windows. Default is...