$dst_category = "UGLY";
$nbs = new NaiveBayesianStorage($_SESSION["uid"]);
- $nb = new NaiveBayesianNgram($nbs);
+ $nb = new NaiveBayesian($nbs);
$result = $this->dbh->query("SELECT score, guid, title, content FROM ttrss_entries, ttrss_user_entries WHERE ref_id = id AND id = " .
$article_id . " AND owner_uid = " . $_SESSION["uid"]);
$owner_uid = $article["owner_uid"];
$nbs = new NaiveBayesianStorage($owner_uid);
- $nb = new NaiveBayesianNgram($nbs);
+ $nb = new NaiveBayesian($nbs);
$categories = $nbs->getCategories();
$bayes_content = mb_strtolower($article["title"] . " " . strip_tags($article["content"]));
- if ($count_neutral >= 5000) {
+ if ($count_neutral >= 10000) {
// enable automatic categorization
$result = $nb->categorize($bayes_content);
+ print_r($result);
+
if (count($result) == 3) {
$prob_good = $result[$id_good];
$prob_bad = $result[$id_bad];
if ($prob_good > 0.90) {
- $dst_category = $id_good; // should we autofile as good or not? idk
+ $dst_category = $id_good;
$article["score_modifier"] += $this->score_modifier;
} else if ($prob_bad > 0.90) {
- $dst_category = $id_bad; // should we autofile as good or not? idk
+ $dst_category = $id_bad;
$article["score_modifier"] -= $this->score_modifier;
}
}
+
+ _debug("bayes, dst category: $dst_category");
}
$nb->train($article["guid_hashed"], $dst_category, $bayes_content);
$this->dbh->query("COMMIT");
$nbs = new NaiveBayesianStorage($_SESSION["uid"]);
- $nb = new NaiveBayesianNgram($nbs);
+ $nb = new NaiveBayesian($nbs);
$nb->updateProbabilities();
}