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Objective Function

Definition of Objective Function An objective function (in machine learning) is a mathematical formula used to calculate the relative merit of each possible solution to a problem. The objective function takes into account the inputs and outputs of a problem, as well as any constraints that may exist. It then calculates a score for each…

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Overfitting

Definition of Overfitting Overfitting: Overfitting is a phenomenon that can occur in machine learning when a model begins to “fit” the training data too closely, resulting in poorer performance on new data. This can be caused by excessive use of complex models or excessively large training sets, and can often be avoided by using more…

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Outlier

Definition of Outlier Outlier: An outlier is a data point that is significantly different from the other points in the dataset. Outliers can be caused by errors in data collection or by natural variations in the data. They can be removed from a dataset before analysis, or they can be studied to learn more about…

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Optimization

Definition of Optimization Optimization: Optimization is the process of making something as good as possible. In data science, this usually means finding the best way to use the data to achieve a goal. This can involve choosing the right algorithm to use, or finding the right settings for that algorithm.

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Operational Definition

Definition of Operational Definition Operational Definition: An operational definition is a specific, quantitative definition of a term, which can be used to measure or calculate it. This definition is typically found in a laboratory setting, where a scientist can observe and measure the term’s properties. For example, the operational definition of the speed of light…

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One-hot encoding

Definition of One-hot encoding One-hot encoding: One-hot encoding is a technique used in machine learning to represent categorical variables as a vector of binary values. In one-hot encoding, each category is represented by a unique integer value, and the remaining values are set to 0. For example, if there are three categories, A, B, and…

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Oblique Sampling

Definition of Oblique Sampling Oblique Sampling: Oblique sampling is a type of non-random sampling technique. It is used when the researcher wants to study a specific population but does not have access to all members of that population. Oblique sampling involves selecting units for the study in a way that is not completely random. The…