Big Data & Data Science at FOM Hochschule Für Oekonomie & Management

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Common Variable Types

Qualitative Variable

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What is a qualitative variable?

Also called categorical variables, take on values that are names or labels e.g. the gender

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What measurement scales are correct?

Nominal scale

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What expresses the nominal scale?

Characteristic attributes can be distinguished, eg gender. A subtype of it with only two categories (eg male/female) is called dichotomous

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What expresses the ordinal scale?

Characteristic attributes can be distinguished and ranked. Eg educational achivement.

! Intervals between the values can neither be compared nor interpreted

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Definition of Experience E?

Is defined as a set of training instances from a dataset that is used by a computer program in order to learn how to execute a task T
eg Experience is obtained by the computer program by playing checkers games against itself

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What is a Task and what is the character?

Defined as a job a computer program has to learn in order to execute it
Learning itself is not considered as a discrete task
eg Teaching a computer in how to play checkers, then playing checkers itself is the Task T

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How does the Loss Function behave if the predictions deviate too much from the actual results?

If for a given set of parameters the predictions deviate too much from the actual results, the loss function will output a higher number compared to predictions that are good

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What expresses the metric scale?

Characteristic attributes can be distinguished and ranked
Intervals can be compared
Metric scale divides further into interval and ratio scale

Ratio Scale has a naturally given point of origin (eg body weight)
Interval scale has an artificially given point of origin (eg calculation times)

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What are the main key facts of reinforcement learning?

Algorithms from the group of reinforcement learning produce agents rather than classical models that receive information from the environment and react to it by performing an action
information that the agent receives from the environment in form of numerical data is called state which is stored and then used for choosing the right action
The result of the action, the agent receives a reward that can be either positive or negative which is then used as a feedback to the agent in order to update its parameters and change its future actions
process of learning and training is a process of trial and error
- agent finds itself in various states and gets punished every time it takes the wrong action and thus starts learning how to take better actions

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Choose the regression algorithm!

linear regression

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To what refers Iterations?

The number of batches need to complete one epoch

For a training set with 1000 instances and a batch size of 250 it would take 4 iterations to complete 1 epoch

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Big Data & Data Science at FOM Hochschule für Oekonomie & Management

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