14 Static & Dynamic Models
14.1 1. Key Message
đź‘Ť Thought conversion 1:
“Soft” communication shares many qualities of “hard” machine learning. “Hard” deep learning is ground-breaking because of, not despite of its “soft” qualities.
14.2 2. Imagine the parameters to a model
- These are the most intuitive dimensions of a model to consider.
- Parameters draw a path from the input to the output and how they interact with each other.
- e.g. X in the following model:
\[y_i = \beta_{0} + \beta_{1} x_{i1} + \cdots + \beta_{p} x_{ip} + \varepsilon_i\]
- Of the known parameters, we aim to define its coefficient, i.e. how much it influences the outcome.
- known & actually measured influencing variables
- Of the know parameters, sometimes this is not possible
- Known influencing variables.
- Some parameters will not even be considered
- Unknown influencing variables
14.3 3. Two extremes
Static/Finite Disciplines | Dynamic/Infinite Disciplines | |
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Classical models (goal/object of discipline) | Seek universal truths, e.g. In the form of natural laws & robust theories | Seeking unified understanding (universal truths are rarer and more difficult to develop) |
Techniques | Closed, controlled environments, where the entirety of a system may be described | Even with closed environments, the infinite complexity of the real world is difficult to capture. At most we can define broad trends and generalizations. |
Certainty | Concrete thinking | Probabilistic thinking |
Approach | Analytical Thinking | Systems thinking |
Logic | Deductive reasoning | Inductive reasoning |
Disciplines | Classical physics & chemistry and to a point molecular genetics | Systems Biology (ecology, earth science) & psychology |
14.4 4. A Scenario
Now imagine the simple actions of two people talking to each other. We can imagine two models are at play for each person depending on what they are doing:
Talking | Listening | |
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Model | Describes an encoder transmiting information. | Describes a decoder receiving information. |
Input | Thought | Speech |
Output | Speech | Thought |
TalkingDescribes a model where an encoder transmitsInput in thoughtoutput is speech ListeningDescribes a model where a decoder receivesinput is speechoutput is thought Input, model and output are Interdependent, constrained contextual. Dynamic/Infinite models are also present in project management, decision making & other areas outside of actual technical work.
14.5 5. In Classical Definitions
Static/Finite models in classically soft disciplines | Dynamic/Infinite models in classically hard disciplines |
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