Page 17 - Demo

%u062c%u0645%u064a%u0639 %u0627%u0644%u062d%u0642%u0648%u0642 %u0645%u062d%u0641%u0648%u0638%u0629 %u0640 %u0627%u0625%u0644%u0639%u062a%u062f%u0627%u0621 %u0639%u0649%u0644 %u062d%u0642 %u0627%u0645%u0644%u0624%u0644%u0641 %u0628%u0627%u0644%u0646%u0633%u062e %u0623%u0648 %u0627%u0644%u0637%u0628%u0627%u0639%u0629 %u064a%u0639%u0631%u0636 %u0641%u0627%u0639%u0644%u0647 %u0644%u0644%u0645%u0633%u0627%u0626%u0644%u0629 %u0627%u0644%u0642%u0627%u0646%u0648%u0646%u064a%u0629174- Numeric Attributes: A numeric attribute is quantitative; that is, it is a measurable quantity, represented in integer or real values, numeric attributes can be: a) Interval-Scaled Attributes: - are measured on a scale of equal-size units. The values of intervalscaled attributes have order and can be positive, 0, or negative, for example: - a temperature attribute in Celsius and Fahrenheit. b) Ratio-Scaled Attributes: - is a numeric attribute with an inherent zeropoint, the values are ordered, and we can also compute the difference between values, as well as the mean, median, and mode, for example: -the Kelvin (K) temperature scale has what is considered a true zeropoint (0%u25e6K = %u2212273.15%u25e6C), years of experience, number of words. 5- Discrete Attributes : has a finite or countably infinite set of values, which may or may not be represented as integers. The attributes hair color, smoker, medical test, and drink size each have a finite number of values, and so are discrete. 6- Continuous Attributes : continuous values are real numbers, whereas numeric values can be either integers or real numbers.) In practice, real values are represented using a finite number of digits. Continuous attributes are typically represented as floatingpoint variables. II. Types of data sets 1- Record Data: Majority of Data Mining work assumes that data is a collection of records (data objects) The most basic form of record data has no explicit relationship among records or data fields, and every record (object) has the same set of attributes. It can be: relational records, data matrix, document data, or transaction data.