Mean squared error

Point estimation performance | Statistical deviation and dispersion | Least squares | Loss functions

In statistics, the mean squared error (MSE) or mean squared deviation (MSD) of an estimator (of a procedure for estimating an unobserved quantity) measures the average of the squares of the errors—that is, the average squared difference between the estimated values and the actual value. MSE is a risk function, corresponding to the expected value of the squared error loss. The fact that MSE is almost always strictly positive (and not zero) is because of randomness or because the estimator does not account for information that could produce a more accurate estimate. In machine learning, specifically empirical risk minimization, MSE may refer to the empirical risk (the average loss on an observed data set), as an estimate of the true MSE (the true risk: the average loss on the actual population distribution). The MSE is a measure of the quality of an estimator. As it is derived from the square of Euclidean distance, it is always a positive value that decreases as the error approaches zero. The MSE is the second moment (about the origin) of the error, and thus incorporates both the variance of the estimator (how widely spread the estimates are from one data sample to another) and its bias (how far off the average estimated value is from the true value). For an unbiased estimator, the MSE is the variance of the estimator. Like the variance, MSE has the same units of measurement as the square of the quantity being estimated. In an analogy to standard deviation, taking the square root of MSE yields the root-mean-square error or root-mean-square deviation (RMSE or RMSD), which has the same units as the quantity being estimated; for an unbiased estimator, the RMSE is the square root of the variance, known as the standard error. (Wikipedia).

IAML8.20 Mean squared error and outliers

From playlist Generalization and Evaluation

Intro to standard error

Brief overview of the standard error. What it represents and how you would find it with a formula.

From playlist Basic Statistics (Descriptive Statistics)

Geometry of the Squared Error Surface

From playlist Least-Squares Problems, Linear Algebra, and Machine Learning

Statistics: Ch 7 Sample Variability (11 of 14) What is "The Standard Error of the Mean"?

Visit http://ilectureonline.com for more math and science lectures! To donate: http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 What is “the standard error of the mean”? It is the standard deviation (of the sampling distribution) of the sample means. Previous

From playlist STATISTICS CH 7 SAMPLE VARIABILILTY

Standard Error of the Estimate used in Regression Analysis (Mean Square Error)

An example of how to calculate the standard error of the estimate (Mean Square Error) used in simple linear regression analysis. This typically taught in statistics. Like us on: http://www.facebook.com/PartyMoreStud... Link to Playlist on Regression Analysis http://www.youtube.com/cour

From playlist Linear Regression.

IAML8.21 Mean absolute error (MAE)

From playlist Generalization and Evaluation

Standard Error of the Mean: Let’s Talk About SEx (12-1)

The Standard error of the mean is the average variability between the sample mean and the population mean that is reasonable to expect simply by chance. It is to the Distribution of Sample Means what the standard deviation is to a single mean of a sample. As sample size increases, the stan

From playlist Sampling Distributions in Statistics (WK 12 - QBA 237)

How to calculate standard error for the sample mean

Standard error for the sample mean formula explained in simple steps.

From playlist Basic Statistics (Descriptive Statistics)

How to find the number of standard deviations that it takes to represent all the data

👉 Learn how to find the variance and standard deviation of a set of data. The variance of a set of data is a measure of spread/variation which measures how far a set of numbers is spread out from their average value. The standard deviation of a set of data is a measure of spread/variation

From playlist Variance and Standard Deviation

Basic Excel Business Analytics #54: Basic Forecasting Methods & Measures of Forecast Error

Download files: https://people.highline.edu/mgirvin/AllClasses/348/348/AllFilesBI348Analytics.htm Learn about some Basic Forecasting Methods: 1) (00 Intro to Time Series and Forecasting 2) (02:10) Naïve Method or Most Recent Method for Forecasting 3) (04:34) Forecast Error and Mean Foreca

From playlist Excel Business Analytics (Forecasting, Linear Programming, Simulation & more) Free Course at YouTube (75 Videos)

Recent advances in high dimensional robust statistics - Daniel Kane

Computer Science/Discrete Mathematics Seminar I Topic: Recent advances in high dimensional robust statistics Speaker: Daniel Kane, University of California, San Diego Date: December 11, 2017 For more videos, please visit http://video.ias.edu

From playlist Mathematics

Deep Learning Lecture 2.4 - Statistical Estimator Theory

Deep Learning Lecture - Estimator Theory 3: - Statistical Estimator Theory - Bias, Variance and Noise - Results for Linear Least Square Regression

From playlist Deep Learning Lecture

Linear regression (3): Normal equations

Closed form solution for mean squared error; normal equations; robustness and other losses

From playlist cs273a

Neural Network Training (Part 2): Neural Network Error Calculation

From http://www.heatonresearch.com. An important part of the training process is error calculation. In this video, see how errors are calculated.

From playlist Neural Networks by Jeff Heaton

Basic Excel Business Analytics #47: SST = SSR + SSE & R Squared & Standard Error of Estimate

Download files: https://people.highline.edu/mgirvin/AllClasses/348/348/AllFilesBI348Analytics.htm Learn: 1) (00:14) What we will do in this video: SST, SSR, SSE, R^2 and Standard Error 2) (00:44) What we did last video 3) (01:11) How do we think about “How good our Estimated Regression Li

From playlist Excel Business Analytics (Forecasting, Linear Programming, Simulation & more) Free Course at YouTube (75 Videos)

Uncertainty propagation b: Sample estimates

(C) 2012-2013 David Liao (lookatphysics.com) CC-BY-SA Standard deviation vs. sample standard deviation Mean vs. sample mean Standard deviation of the mean vs. standard error of the mean Rule of thumb for thinking about whether error bars overlap

From playlist Probability, statistics, and stochastic processes

Mean Squared Error | What Is Mean Squared Error? | Probability And Statistics | Simplilearn

In this Probability and Statistics tutorial, you will learn one of the key metrics of Machine Learning, i.e., Mean Squared Error. Then, we will learn how to calculate the mean square error and why it is helpful with the help of an example. 🔥Free Data Science Course with Completion Certifi

Mod-12 Lec-33 Regression Models with Autocorrelated Errors

Regression Analysis by Dr. Soumen Maity,Department of Mathematics,IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in

From playlist IIT Kharagpur: Regression Analysis | CosmoLearning.org Mathematics

Lec 4 | MIT 18.085 Computational Science and Engineering I

Applications to linear estimation: least squares A more recent version of this course is available at: http://ocw.mit.edu/18-085f08 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

From playlist MIT 18.085 Computational Science & Engineering I, Fall 2007

How to find the variance and standard deviation from a set of data

From playlist Variance and Standard Deviation

Mean squared error

Related pages