· Code for mapping db selection to the class using System; using System.Collections.Generic; using System.Data; using System.Reflection; namespace DataSourceLib { public class DataSource { private DataSource() { } public DataSource(DataSet data) { if (data == null ) { data = new DataSet(); } dataSet = data; } private DataSet dataSet { set ; get ; } public IList<T> GetList< T >() { List<T> list = new List<T>(); try { DataTable dt = dataSet.Tables[0]; foreach (DataRow dr in dt.Rows) { T obj = (T)Activator.CreateInstance( typeof (T)); PropertyInfo[] propertyInfos; propertyInfos = obj.GetType().GetProperties(); for ( int i = 0; i < data
you start with the data that contains patterns. you can feed that data to the machine learning algorithm (may be more algorithms) to find the patterns in the data .This algorithm generates something called a model.Model functionality is to recognizes the patterns then presented with the new data. Application supplies new data to see if it matches known patterns such as the data about new transactions. The model can determine the probability whether the transaction is fraudulent or not, it knows that because of the patterns. Machine learning lets us find patterns in existing data, then create and use a model that recognizes those patterns in new data Machine learning has gone mainstream - big vendors think there's big money in this market Machine learning can probably help your organization.