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Data Structure Articles
Page 145 of 164
Difference between Dimensionality Reduction and Numerosity Reduction?
Dimensionality ReductionIn dimensionality reduction, data encoding or transformations are used to access a reduced or “compressed” depiction of the original data. If the original data can be regenerated from the compressed data without any loss of data, the data reduction is known as lossless. If data reconstructed is only approximated of the original data, then the data reduction is called lossy.The DWT is nearly associated with the discrete Fourier transform (DFT), a signal processing technique containing sines and cosines. In general, the DWT achieves better lossy compression. That is if a similar number of coefficients is maintained for a DWT ...
Read MoreWhat is Numerosity Reduction?
In the Numerosity reduction, the data volume is reduced by choosing an alternative, smaller form of data representation. These techniques may be parametric or nonparametric. For parametric methods, a model is used to estimate the data, so that only the data parameters need to be stored, instead of the actual data, for example, Log-linear models. Non-parametric methods are used for storing a reduced representation of the data which include histograms, clustering, and sampling.There are the following techniques of numerosity reduction which are as follows −Regression and Log-Linear Models − These models can be used to approximate the given data. In ...
Read MoreWhat is the basic method of attribute subset selection?
Attribute subset selection decreases the data set size by eliminating irrelevant or redundant attributes (or dimensions). Attribute subset selection aims to discover a minimum set of attributes such that the resulting probability distribution of the data classes is as close as applicable to the original distribution accessing using all attributes. Data mining on a reduced set of attributes has an extra benefit. It reduces the multiple attributes occurring in the discovered patterns, provides to create the patterns simpler to understand.For n attributes, there are 2n possible subsets. An exhaustive search for the optimal subset of attributes can be intensely expensive, ...
Read MoreWhat is Data Reduction?
Data mining is applied to the selected data in a large amount database. When data analysis and mining is done on a huge amount of data then it takes a very long time to process, which makes it impractical and infeasible. It can reduce the processing time for data analysis, data reduction techniques are used to obtain a reduced representation of the dataset that is much smaller in volume by maintaining the integrity of the original data. By reducing the data, the efficiency of the data mining process is improved which produces the same analytical results.Data reduction aims to define ...
Read MoreWhat is Data Transformation?
In data transformation, the data are transformed or combined into forms suitable for mining. Data transformation can involve the following −Smoothing − It can work to remove noise from the data. Such methods contain binning, regression, and clustering.Aggregation − In aggregation, where summary or aggregation operations are applied to the data. For example, the daily sales data may be aggregated to compute monthly and annual total amounts. This phase is generally used in making a data cube for the analysis of the data at multiple granularities.Generalization − In Generalization, where low-level or “primitive” (raw) data are restored by larger-level concepts ...
Read MoreWhat is Data Cleaning?
Data cleaning defines to clean the data by filling in the missing values, smoothing noisy data, analyzing and removing outliers, and removing inconsistencies in the data. Sometimes data at multiple levels of detail can be different from what is required, for example, it can need the age ranges of 20-30, 30-40, 40-50, and the imported data includes birth date. The data can be cleans by splitting the data into appropriate types.Types of data cleaningThere are various types of data cleaning which are as follows −Missing Values − Missing values are filled with appropriate values. There are the following approaches to ...
Read MoreWhat is the motivation behind data mining?
Data mining is the procedure of finding useful new correlations, patterns, and trends by sharing through a high amount of data saved in repositories, using pattern recognition technologies including statistical and mathematical techniques. It is the analysis of factual datasets to discover unsuspected relationships and to summarize the records in novel methods that are both logical and helpful to the data owner.It is the procedure of selection, exploration, and modeling of high quantities of information to find regularities or relations that are at first unknown to obtain clear and beneficial results for the owner of the database.It is not limited ...
Read MoreWhat Kinds of data can be mined?
Data mining defines extracting or mining knowledge from huge amounts of data. Data mining is generally used in places where a huge amount of data is saved and processed. For example, the banking system uses data mining to save huge amounts of data which is processed constantly.In Data mining, hidden patterns of data are considering according to the multiple categories into a piece of useful data. This data is assembled in an area including data warehouses for analyzing it, and data mining algorithms are performed. This data facilitates in creating effective decisions which cut value and increase revenue.There are various ...
Read MoreDifference Between SATA and PATA
In this post, we will understand the difference between SATA and PATA −PATAIt stands for Parallel Advanced Technology Attachment.It is a 40 pin connector.It is expensive.The speed of data transfer is low.It consumes more power.The size of the cable is big.It doesn’t come with hot swapping feature.External hard drives can’t be used with PATA.SATAIt stands for Serial Advanced Technology Attachment.It is a 7 pin connector.It is cheap.The speed of data transfer is high.It consumes less power.The size of the cable is small.It comes with the hot swapping feature.External hard drives can be used with SATA.
Read MoreDifference Between USART and UART
In this post, we will understand the difference between USART and UART modes −USART (Universal Synchronous/Asynchronous Receiver/Transmitter)The half-duplex mode is used.The speed of USART is more in comparison to UART.It uses data signals as well as clock to work.The data is transmitted in the format of blocks.It can work similar to UART.It is more complex in comparison to UART.The receiver doesn’t require to know the baud-pace of the transmitter.This is because it gets information by the master and the clock signal.The data is transmitted at a definite (specific) rate.UART (Universal Asynchronous Receiver/Transmitter)It uses full-duplex mode.Its speed is less in comparison ...
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