'Get the statistics for items with a particular key
>>> tracker = Tracking()
>>> tracker.add(\'log_perplexity\', 55.6)
>>> tracker.add(\'log_perplexity\', 55.2)
>>> tracker.stats(\'log_perplexity\')
(55.400000000000006, 0.19999999999999929, 0.0)'

def stats(self, key):

    data = self.cache[key]
    mean = np.mean(data)
    std = np.std(data)
    slope = self.slope
    if ((self.calls % 100) == 0):
        lr = LinearRegression()
        x = np.arange(len(data)).astype('float32')
        lr.fit(x[:, None], np.array(data))
        self.slope = lr.coef_[0]
    self.calls += 1
    return (mean, std, slope)
