Classification is important problem in data mining. Given a data set, classifier generates meaningful description for each class. Decision trees are most effective and widely used classification methods. There are several algorithms for induction of decision trees. These trees are first induced and then prune subtrees with subsequent pruning phase to improve accuracy and prevent overfitting. In this paper, various pruning methods are discussed with their features and also effectiveness of pruning is evaluated. Accuracy is measured for diabetes and glass dataset with various pruning factors. The experiments are shown for this two datasets for measuring accuracy and size of the tree.

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This paper presents a 5 -bit 4.87GSps Flash ADC design using 45-nm GPDK CMOS technology library. The designed system consists of two main blocks as comparator array and digital decoder. The digital decoder contains 2:1 MUX based 1 -of -N decoder and Regenerative Buffer units. As a result, active die area and the power consumption are reduced in addition to increase in sampling frequency. The power supply voltage range for the overall system is ± 1.8V. The simulation results include maximum power consumption of 0.24 mW. The Conversion time 204p sec, the measured DNL and INL to less than 0.02LSB and 0.1LSB.

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