def doTargetPrediction(pickled_model_name):
	if os.name == 'nt': sep = '\\'
	else: sep = '/'
	mod = pickled_model_name.split(sep)[-1].split('.')[0]
	clf = open_Model(mod)
	preds1 = sum(clf.predict_proba(querymatrix1)[:,1] > threshold)
	preds2 = bg_preds[mod]
	oddsratio, pvalue = stats.fisher_exact([[preds2,2000000-preds2],[preds1,len(querymatrix1)-preds1]])
	try:
		ratio, preds1_percentage, preds2_percentage = calcPredictionRatio(preds1,preds2)
		return ratio, mod, preds1, preds1_percentage, preds2, preds2_percentage, oddsratio, pvalue
	except TypeError: return None