Regression is a method by which a functional
relationship in the real world may be described by a mathematical model which
may then, like all models, may be used to explore, describe or predict the
relationship.
The method of least squares, published in 1805, showed the orbits of astrological bodies about the sun. The observations of planets and comets,using regression techniques, began to further the science. The term regression was coined in the 19th century to describe a biological phenomenon. The heights of descendants of tall ancestors would regress downward toward a normal average would become known as regression toward the mean.
The method of least squares, published in 1805, showed the orbits of astrological bodies about the sun. The observations of planets and comets,using regression techniques, began to further the science. The term regression was coined in the 19th century to describe a biological phenomenon. The heights of descendants of tall ancestors would regress downward toward a normal average would become known as regression toward the mean.
Linear regression
Linear regression The degrees of freedom number in the Regression line is the number of predictors used. Here that number is 1, and the regression has a single predictor.
Linear regression The degrees of freedom number in the Regression line is the number of predictors used. Here that number is 1, and the regression has a single predictor.
Multiple regression analysis models can be used to
observe the algebraic formula : (y = a
+ bc)
When using these math techniques, Using multi-tier tests to
bring the model into balance, always seems to me like a symphony of music. Turns
out it is allot like music, but in the form of algorithms.
Machine
learning is a scientific discipline that explores the construction
and study of algorithms that can learn from data. Such algorithms operate by
building a model based on inputs and using that to make predictions or
decisions, rather than following only explicitly programmed instructions.Machine
learning can be considered a subfield of computer science and statistics. It
has strong ties to artificial intelligence and optimization, which deliver
methods, theory and application domains to the field. Machine learning is
employed in a range of computing tasks where designing and programming
explicit, rule-based algorithms is infeasible. Example applications include
spam filtering, optical character recognition search engines and computer
vision. Machine learning is sometimes conflated with data mining, although that
focuses more on exploratory data analysis.Machine learning and pattern
recognition "can be viewed as two facets of the same field.
Finally, the foundations of this science, have the
constant balance necessary to allow observations to be made. Observing such
discoveries as the golden ratio,the zero,PHI +, phi -,irrational numbers,
Solfeggio scale of music,and the Fibonacci sequence in nature and more. The
multiple layers of perfection of this science have been unfolding since the Egyptians
and the Greeks,Hindu sanskriti, I Ching Hexagrams,started to unfold into human
knowledge and allow the meta- knowledge that we see today.