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TM.anomaly: fix score for likelihood anomaly modes #666

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TM.anomaly: fix score for likelihood anomaly modes #666

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TM.anomaly: improve doc for anomaly modes
breznak Sep 16, 2019
9c1a2cf
Merge branch 'master_community' into anomaly_likelihood_docs
breznak Sep 18, 2019
9e0245f
TM.anomaly: fix scores for likelihoods
breznak Sep 18, 2019
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2 changes: 1 addition & 1 deletion src/htm/algorithms/TemporalMemory.cpp
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Expand Up @@ -515,7 +515,7 @@ void TemporalMemory::compute(const SDR &activeColumns,
cellsToColumns( getPredictiveCells() ));
const Real like = tmAnomaly_.anomalyLikelihood_.anomalyProbability(raw);
const Real log = tmAnomaly_.anomalyLikelihood_.computeLogLikelihood(like);
tmAnomaly_.anomaly_ = log;
tmAnomaly_.anomaly_ = log; //TODO loglike is `log(1 - likelihood)/log(epsilon)`, should we return 1-loglike to be consistent with "anomalies"? (high score for anomalous inputs).
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} break;
// TODO: Update mean & standard deviation of anomaly here.
};
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19 changes: 17 additions & 2 deletions src/htm/algorithms/TemporalMemory.hpp
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Expand Up @@ -688,8 +688,23 @@ class TemporalMemory : public Serializable
* anomaly score computed for the current inputs
* (auto-updates after each call to TM::compute())
*
* @return a float value from computeRawAnomalyScore()
* from Anomaly.hpp
* Note, if you use manual learning methods for TM (activateDendrites, etc.) the scores
* will not be in sync (works only if `TM.compute` is used).
*
* Options `ANMode` {DISABLED, RAW, LIKELIHOOD, LOGLIKELIHOOD} passed during constructor
* of this class affect the computation of anomaly here.
* - "DISABLED": always returns 0.5f, no computation is performed (use if you don't care for anomaly
* and need maximum speed).
* - "RAW": return value from `computeRawAnomalyScore()` from `Anomaly.hpp`, default.
* - "LIKELIHOOD": Compute the probability that the current anomaly score represents
* an anomaly given the historical distribution of anomaly scores. The closer
* the number is to 1, the higher the chance it is an anomaly.
* Computed from `anomalyProbability()` in `AnomalyLikelihood.hpp`.
* - "LOGLIKELIHOOD": Compute a log scale representation of the likelihood value. This mode performs
* `computeLogLikelihood()` from `AnomalyLikelihood.hpp`
*
* @return a float value based on `ANMode` argument used in constructor of the TM class.
* By default return value from `computeRawAnomalyScore()` from `Anomaly.hpp`
*/
const Real &anomaly = tmAnomaly_.anomaly_; //this is position dependant, the struct anomaly_tm must be defined before this use,
// otherwise this surprisingly compiles, but a call to `tmAnomaly_.anomaly` segfaults!
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