Whenever we discuss model prediction, it’s important to understand prediction errors (bias and variance). There is a tradeoff between a model’s ability to minimize bias and variance. Gaining a proper understanding of these errors would help us not only to build accurate models but also to avoid the mistake of overfitting and underfitting. Show
So let’s start with the basics and see how they make difference to our machine learning Models. What is bias? Bias is the difference between the average prediction of our model and the correct value which we are trying to predict. Model with high bias pays very little attention to the training data and oversimplifies the model. It always leads to high error on training and test data. What is variance? Variance is the variability of model prediction for a given data point or a value which tells us spread of our data. Model with high variance pays a lot of attention to training data and does not generalize on the data which it hasn’t seen before. As a result, such models perform very well on training data but has high error rates on test data. Mathematically Let the variable we are trying to predict as Y and other covariates as X. We assume there is a relationship between the two such that Y=f(X) + e Where e is the error term and it’s normally distributed with a mean of 0. We will make a model f^(X) of f(X) using linear regression or any other modeling technique. So the expected squared error at a point x is The Err(x) can be further decomposed as Err(x) is the sum of Bias², variance and the irreducible error. Irreducible error is the error that can’t be reduced by creating good models. It is a measure of the amount of noise in our data. Here it is important to understand that no matter how good we make our model, our data will have certain amount of noise or irreducible error that can not be removed. Bias and variance using bulls-eye diagram In the above diagram, center of the target is a model that perfectly predicts correct values. As we move away from the bulls-eye our predictions become get worse and worse. We can repeat our process of model building to get separate hits on the target. In supervised learning, underfitting happens when a model unable to capture the underlying pattern of the data. These models usually have high bias and low variance. It happens when we have very less amount of data to build an accurate model or when we try to build a linear model with a nonlinear data. Also, these kind of models are very simple to capture the complex patterns in data like Linear and logistic regression. In supervised learning, overfitting happens when our model captures the noise along with the underlying pattern in data. It happens when we train our model a lot over noisy dataset. These models have low bias and high variance. These models are very complex like Decision trees which are prone to overfitting. Why is Bias Variance Tradeoff? If our model is too simple and has very few parameters then it may have high bias and low variance. On the other hand if our model has large number of parameters then it’s going to have high variance and low bias. So we need to find the right/good balance without overfitting and underfitting the data. This tradeoff in complexity is why there is a tradeoff between bias and variance. An algorithm can’t be more complex and less complex at the same time. Total Error To build a good model, we need to find a good balance between bias and variance such that it minimizes the total error. An optimal balance of bias and variance would never overfit or underfit the model. Therefore understanding bias and variance is critical for understanding the behavior of prediction models. Only RFID Journal provides you with the latest insights into what’s happening with the technology and standards and inside the operations of leading early adopters across all industries and around the world. To stay informed and take advantage of all of the unique resources RFID Journal offers become a member today.Real estate is property consisting of land and the buildings on it, along with its natural resources such as crops, minerals or water; immovable property of this nature; an interest vested in this (also) an item of real property, (more generally) buildings or housing in general.[1][2] In terms of law, real is in relation to land property and is different from personal property while estate means the "interest" a person has in that land property.[3] Real estate is different from personal property, which is not permanently attached to the land, such as vehicles, boats, jewelry, furniture, tools and the rolling stock of a farm. In the United States, the transfer, owning, or acquisition of real estate can be through business corporations, individuals, nonprofit corporations, fiduciaries, or any legal entity as seen within the law of each U.S. state.[4] History of real estateThe natural right of a person to own property as a concept can be seen as having roots in Roman law as well as Greek philosophy.[5] The profession of appraisal can be seen as beginning in England during the 1500s as agricultural needs required land clearing and land preparation. Textbooks on the subject of surveying began to be written and the term "surveying" was used in England, while the term "appraising" was more used in North America.[6] Natural law which can be seen as "universal law" was discussed among writers of the 15th and 16th century as it pertained to "property theory" and the inter-state relations dealing with foreign investments and the protection of citizens private property abroad. Natural law can be seen as having an influence in Emerich de Vattel's 1758 "Law of Nations" which conceptualized the idea of private property.[7] One of the largest initial real estate deals in history known as the "Louisiana Purchase" happened in 1803 when the Louisiana Purchase Treaty was signed. This treaty paved the way for western expansion and made the U.S. the owners of the "Louisiana Territory" as the land was bought from France for fifteen million, making each acre roughly 4 cents.[8] The oldest real estate brokrage firm was established in 1855 in Chicago, Illinois, and was initially known as "L. D. Olmsted & Co." but is now known as "Baird & Warner."[9] In 1908, the National Association of Realtors was founded in Chicago and in 1916, the name was changed to the National Association of Real Estate Boards and this was also when the term "realtor" was coined to identify real estate professionals.[10] The stock market crash of 1929 and the Great Depression in the U.S. caused a major drop in real estate worth and prices and ultimately resulted in depreciation of 50% for the four years after 1929.[11] Housing financing in the U.S. was greatly affected by the Banking Act of 1933 and the National Housing Act in 1934 because it allowed for mortgage insurance for home buyers and this system was implemented by the Federal Deposit Insurance as well as the Federal Housing Administration.[12] In 1938, an amendment was made to the National Housing Act and Fannie Mae, a government agency, was established to serve as a secondary market for mortgages and to give lenders more money in order for new homes to be funded.[13] Title VIII of the Civil Rights Act in the U.S., which is also known as the Fair Housing Act, was put into place in 1968 and dealt with the incorporation of African Americans into neighborhoods as the issues of discrimination were analyzed with the renting, buying, and financing of homes.[14] Internet real estate as a concept began with the first appearance of real estate platforms on the World Wide Web and occurred in 1999. Residential real estateResidential real estate may contain either a single family or multifamily structure that is available for occupation or for non-business purposes.[15] Residences can be classified by and how they are connected to neighbouring residences and land. Different types of housing tenure can be used for the same physical type. For example, connected residences might be owned by a single entity and leased out, or owned separately with an agreement covering the relationship between units and common areas and concerns.[16] According to the Congressional Research Service, in 2021, 65% of homes in the U.S. are owned by the occupier.[17] Major categories
The size of an apartment or house can be described in square feet or meters. In the United States, this includes the area of "living space", excluding the garage and other non-living spaces. The "square meters" figure of a house in Europe may report the total area of the walls enclosing the home, thus including any attached garage and non-living spaces, which makes it important to inquire what kind of surface area definition has been used. It can be described more roughly by the number of rooms. A studio apartment has a single bedroom with no living room (possibly a separate kitchen). A one-bedroom apartment has a living or dining room separate from the bedroom. Two bedroom, three bedroom, and larger units are common. (A bedroom is a separate room intended for sleeping. It commonly contains a bed and, in newer dwelling units, a built-in closet for clothes storage.) Other categories The size of havelis and chawls is measured in Gaz (square yards), Quila, Marla, Beegha, and acre. See List of house types for a complete listing of housing types and layouts, real estate trends for shifts in the market, and house or home for more general information. Real estate and the environmentReal estate can be valued or devalued based on the amount of environmental degradation that has occurred. Environmental degradation can cause extreme health and safety risks. There is a growing demand for the use of site assessments (ESA's) when valuing a property for both private and commercial real estate.[18] Environmental surveying is made possible by environmental surveyors who examine the environmental factors present within the development of real estate as well as the impacts that development and real estate has on the environment. Green development is a concept that has grown since the 1970s with the environmental movement and the World Commission on Environment and Development. Green development examines social and environmental impacts with real estate and building. There are 3 areas of focus, being the environmental responsiveness, resource efficiency, and the sensitivity of cultural and societal aspects. Examples of Green development are green infrastructure, LEED, conservation development, and sustainability developments. Real estate in itself has been measured as a contributing factor to the rise in green house gases. According to the International Energy Agency, real estate in 2019 was responsible for 39 percent of total emissions worldwide and 11 percent of those emissions were due to the manufacturing of materials used in buildings.[19] As an investmentA house that was sold in Victoria Australia In markets where land and building prices are rising, real estate is often purchased as an investment, whether or not the owner intends to use the property. Often investment properties are rented out, but "flipping" involves quickly reselling a property, sometimes taking advantage of arbitrage or quickly rising value, and sometimes after repairs are made that substantially raise the value of the property. Luxury real estate is sometimes used as a way to store value, especially by wealthy foreigners, without any particular attempt to rent it out. Some luxury units in London and New York City have been used as a way for corrupt foreign government officials and businesspeople from countries without strong rule of law to launder money or to protect it from seizure.[20] Which two control charts are typically used together?The Range (R) and Standard Deviation (S) control charts are typically used together with the X-bar chart (See Control Chart #2) to evaluate process variation.
Which of the following indicates the process is out of control?A process is said to be out of control if: One or more data points fall outside the control limits. Seven consecutive data points increasing or decreasing. Eight consecutive data points are on one side of average.
Which letter denotes the maximum number of defective items that can be found in the sample before the lot is rejected multiple choice question?'AQL' stands for 'Acceptance Quality Limit', and is defined as the “quality level that is the worst tolerable” in ISO 2859-1. It represents the maximum number of defective units, beyond which a batch is rejected. Importers usually set different AQLs for critical, major, and minor defects.
Which of the following companies made process capability and product design famous by adopting Six Sigma limits?Motorola made process capability and product design famous by adopting its now well-known six-sigma limits.
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