Koller and Friedman write in "Probabilistic Graphical Models" about the "clarity test", so that state variables should be clear for an all seeing observer.
States like "human_activity" are not objectively measurable.
Fairly PGMs and causal models are not the same, but this way of thinking about state variables is an incredible good filter.
Comments
Koller and Friedman write in "Probabilistic Graphical Models" about the "clarity test", so that state variables should be clear for an all seeing observer.
States like "human_activity" are not objectively measurable.
Fairly PGMs and causal models are not the same, but this way of thinking about state variables is an incredible good filter.
Well, or at least they would need a heavy dose of operationalisation.