Overfitting


Overfitting
A modeling error which occurs when a function is too closely fit to a limited set of data points. Overfitting the model generally takes the form of making an overly complex model to explain idiosyncrasies in the data under study. In reality, the data being studied often has some degree of error or random noise within it. Thus attempting to make the model conform too closely to slightly inaccurate data can infect the model with substantial errors and reduce its predictive power.

Financial professionals must always be aware of the dangers of overfitting a model based on limited data. For instance, a common problem is using computer algorithms to search extensive databases of historical market data in order to find patterns. Given enough study, it is often possible to develop elaborate theorems which appear to predict things such as returns in the stock market with close accuracy. However, when applied to data outside of the sample, such theorems may likely prove to be merely an overfitting of a model to what were in reality just chance occurrences. In all cases, it is important to test a model against data which is outside of the sample used to develop it.


Investment dictionary. . 2012.

Look at other dictionaries:

  • Overfitting — Noisy (roughly linear) data is fitted to both linear and polynomial functions. Although the polynomial function passes through each data point, and the linear function through few, the linear version is a better fit. If the regression curves were …   Wikipedia

  • Overfitting — blau: Fehler bzgl. Trainingsdatensätzen rot: Fehler bzgl. Testdatensätzen Wenn der Fehler bzgl. der Testdatensätze steigt, während der Fehler bzgl. der Trainingsdatensätze stetig fällt, dann befindet man sich möglicherweise in einer… …   Deutsch Wikipedia

  • Overfitting — Surapprentissage Surapprentissage dans un apprentissage supervisé. En rouge, l erreur sur l ensemble de validation. En bleu, l erreur d apprentissage. Si l erreur de validation augmente alors que l erreur d apprentissage continue à diminuer alors …   Wikipédia en Français

  • overfitting — noun The action of the verb …   Wiktionary

  • Overfitting (machine learning) — For the statistical concept see OverfittingThe concept of overfitting is important in machine learning. Usually a learning algorithm is trained using some set of training examples, i.e. exemplary situations for which the desired output is known.… …   Wikipedia

  • Überanpassung — blau: Fehler bzgl. Trainingsdatensätzen rot: Fehler bzgl. Testdatensätzen Wenn der Fehler bzgl. der Testdatensätze steigt, während der Fehler bzgl. der Trainingsdatensätze stetig fällt, dann befindet man sich möglicherweise in einer… …   Deutsch Wikipedia

  • Slope One — Este artículo está huérfano, pues pocos o ningún artículo enlazan aquí. Por favor, introduce enlaces hacia esta página desde otros artículos relacionados …   Wikipedia Español

  • Experimental economics — is a the application of experimental methods to study economic questions. Experiments are used to test the validity of economic theories and test bed new market mechanisms. Using cash motivated subjects, economic experiments create real world… …   Wikipedia

  • Regularization (mathematics) — For other uses in related fields, see Regularization (disambiguation). In mathematics and statistics, particularly in the fields of machine learning and inverse problems, regularization involves introducing additional information in order to… …   Wikipedia

  • Slope One — Collaborative filtering is a technique used by recommender systems to combine different users opinions and tastes in order to achieve personalized recommendations. There are at least two classes of collaborative filtering: user based techniques… …   Wikipedia


Share the article and excerpts

Direct link
Do a right-click on the link above
and select “Copy Link”

We are using cookies for the best presentation of our site. Continuing to use this site, you agree with this.