The Recordset was not XML-based and could not be serialized to XML easily or flexibly.
Finally, a Recordset was not independent of a data store because it tracked a Connection object
and through its methods could send queries to the data source to populate, update,
and refresh its data.
To that end, the Recordset contained functionality found in the ADO.NET DataSet,
data reader, and data adapter objects.
Similar to the DataSet, a Recordset could be disconnected from its data store
and therefore act as an in-memory cache of data.
Of course, it could also be used in a connected model depending on the cursor options that were set.
Although the Recordset object stored multiple versions of each column for each of its rows,
it was not by nature able to represent multiple tables without the use of the Data Shape Provider.
dataset is a ado.net object .it is adisconnected
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datareader is a ado.net object .it is connected
To find the maximum error in a dataset, calculate the difference between each data point and the true value, then identify the largest difference as the maximum error.
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The property that indicates a DataReader is open is the IsClosed property. If IsClosed returns false, it means the DataReader is currently open and can be used to read data. Conversely, if IsClosed returns true, the DataReader is closed and cannot be used to retrieve data.
The range of a single data point, such as 345678, cannot be determined because the range typically requires a set of values. The range is calculated as the difference between the maximum and minimum values in a dataset. If you have a dataset that includes multiple values, please provide them for a specific range calculation.
The geometric mean is calculated by multiplying all the numbers in a dataset and then taking the nth root, where n is the number of values. The average, also known as the arithmetic mean, is calculated by adding all the numbers in a dataset and then dividing by the number of values. The main difference is that the geometric mean considers the product of the values, while the average considers the sum of the values.
A correlation diagram visually represents the relationship between variables in a dataset. It shows how strongly and in what direction variables are related to each other.
The total deviation formula used to calculate the overall variance in a dataset is the sum of the squared differences between each data point and the mean of the dataset, divided by the total number of data points.
The keyword "frequency" refers to how often a particular value appears in a dataset. The variation in data points within a dataset is related to how spread out or diverse the values are. Higher frequency of certain values can indicate less variation, while lower frequency can indicate more variation in the dataset.
There are 4 data set classes: 1) DataSet Constructor 2)DataSet Properties 3)DataSet Methods 4)DataSet Events
A dataset is a group of information used to determain a hypothesis.
AI face detection dataset