Time series anomaly detection combined with data anomaly detection
<p>I'm working on a data anomaly detection system and I've tried so far the two following approaches:</p>

<ul>
<li>Supervised (one class SVM)</li>
<li>Unsupervised (K-means)</li>
</ul>

<p>But I'm having trouble to come up with an algorithm that detects date time anomalies, like for example there can't be a register with the date 12/3/2016 after the date 12/4/2013.
Can you point me to some algorithm, link, whatever that can learn the pattern in a time series that can be somehow combined with the previous approaches?</p>

<p>I'm not asking for a super specific solution but for an advice on some approach that might help me overcome this issue.</p>