kjgxcs
False
Data mining is effectively storing and analysing old pieces of data and predicting what's going to happened in future based on trends and patterns in that data.
Inferring means when you explain or interpret the things you observe. Predicting means is when you predict that something is gonna happen. It's like a 50/50 chance it will happen, your predicting it. I think they are similar because you are both explaining what is gonna happen. For Inferring you're explaining the things that you have observed and for predicting you are explaining something that you think will happen. You both have evidence to back up the problem. AND THEN YOU WILL SUCK MY COCK
It measures the error or variability in predicting Y.
samplingsampling
Predicting data between two known pieces is called forecasting. This is commonly applied in business planning and can be used as the basis for critical decisions.
False
Data mining is effectively storing and analysing old pieces of data and predicting what's going to happened in future based on trends and patterns in that data.
Calculated data is data attained from a theory and or formula. Raw data is data accumulated from an observation or experiment. If the calculated data from a theory is successful in predicting the raw data of an observation/experiment, then the theory is strengthened.
what are 2 kind of predicting what are 2 kind of predicting what are 2 kind of predicting what are 2 kind of predicting what are 2 kind of predicting what are 2 kind of predicting what are 2 kind of predicting what are 2 kind of predicting what are 2 kind of predicting what are 2 kind of predicting what are 2 kind of predicting what are 2 kind of predicting what are 2 kind of predicting what are 2 kind of predicting what are 2 kind of predicting
interpolation, because we are predicting from data in the range used to create the least-squares line.
If you are predicting a point that's outside of the data range, it is known as extrapolation. If it is within the data range it is interpolation and is much more reliable.
They map faults, detect changes along faults, and develop a method of predicting earthquakes
Predicting variables are variables used in statistical and machine learning models to predict an outcome or target variable. These variables are used to forecast or estimate the value of the target variable based on their relationships and patterns in the data. Selecting relevant predicting variables is important for building accurate and effective predictive models.
what is predicting outline
Models for predicting weather rely heavily on using past meteorological data for development and testing.
They map faults, detect changes along faults, and develop a method of predicting earthquakes