کیوں اس طرح کی صورتِ حالات ہو گئی
مشکل ہی دوستوں سے ملاقات ہو گئی
زلفیں ہٹیں جو رُخ سے تو روشن ہوا تھا دن
واپس ہوئیں تو دیکھیے پھر رات ہو گئی
اک بے وفا کی یاد بھلانے کو زندگی
افسوس یہ کہ نذرِ خرابات ہو گئی
سارے جہاں نشاط کے جب اس کے ہو گئے
پھر رنج و غم کی دنیا مرے ساتھ ہو گئی
تائبؔ کچھ اس طرح سے میں رویا ہوں رات بھر
لگتا ہے جیسے شہر میں برسات ہو گئی
The foundation of the Sharia is revelation, revelation is the name of two things, the Qur'an and the Sunnah, since both are related to the news, and to convey the news to others, narrators are needed, so for the propagation of the Qur'an and the Sunnah to future generations. It was necessary to have narrators, the narrators of the Holy Qur'an are called Qira, the narrators of the Sunnah are called Muhaddith, the traditions of the Holy Qur'an are called 'Qara'at' and the traditions of the Sunnah are called 'Ahadith'.
Both the Qur'an and the Sunnah are revelations, but still there are some differences between them which are explained in detail in the Book of Principles. It was a difficult task, and the significant efforts made by the Muhadditheen in this regard were more famous and campaigned than the knowledge of al-Qaraat and recitation. He became famous with this, and some people even got the wrong impression that he had nothing to do with jurisprudence, and this wrong impression was reinforced by the behavior of the some Narrators.
In reasoning and deriving from the Sunnah, there were many disorders and factors that gave birth to different schools of jurisprudence. For example, a hadith revealed to an imam or a jurist during reasoning has a hidden reason that is not revealed to anyone else. Therefore, there is a difference in argumentation. Similarly, sometimes the hadeeth is correct in a certain issue in front of a jurist, while on the other hand, it is weak in the opinion of another, which leads to diversity in argumentation.
When the jurists differed in the derivation of the issues and rulings, in fact, these are cases of priority and non-priority, in which there is, however, scope that any position can be declared preferred based on arguments.
Keywords: Hadith, Muhaddithin, Jurisprudential Proverbs, School of Thoughts, Differences.
Telecommunication industry has grown rapidly during the last decade. The number of cellular subscribers is approaching about 96% of total population of the world. In such a fierce competition, telecom service providers are facing saturated markets with little room for penetration. Therefore, telecom companies are focusing more on customer retention, which is considered cost effective as compared to adding new customers. Moreover, customer retention is more economical as it does not involve any additional marketing expense. Long term customers are also considered as easier to serve, contribute more toward stable profitability, and introduce new referrals as well. On the other hand, new customers are hard to be attracted in competitive markets and take little longer for establishing loyalties with the new service providers. Therefore, telecom industry requires a reliable churn prediction system, which accurately identifies the customers who are about to switch over to another service provider. The role of customer churn prediction system has become pivotal in retaining customers expected to churn by luring them with the improved service packages. This preceding knowledge of customers‟ churning would enable service providers to avoid sizeable revenue losses. Consequently for churn prediction, researchers have investigated many interesting data mining techniques that can meet the specific demands of telecom industry. However, the telecom churn prediction is still a challenging tak because of the the big size, imbalanced class distribution, and high dimensionality of telecom datasets. The main focus of this thesis is to identify discriminative feature extraction techniques and effective sampling methods to cater for the enormous nature of telecom datasets. Additionally, investigations are made to develop a churn prediction system with better classification and interpreting capabilities. This thesis makes the following contributions in the area of telecom churn prediction: 1) Analysis of minimum redundancy and maximum relevance (mRMR) method for extracting relevant and meaningful features, 2) Exploiting Genetic Algorithm based wrapper method to remove any redundant features from selected features, 3) Analysis of PSO xvi based intelligent sampling technique and its comparison to conventional undersampling techniques, 4) Constructing efficient churn prediction systems using computational intelligence based ensemble classification approaches (CP-MRF, Chr-mRF FEW-ChrP), 5) Employing novel GP-AdaBoost based ensemble classifier to develop an efficient churn prediction system with the additional capability of identifying factors responsible for churning, 6) Attaining highest churn prediction performance of 0.862 AUC and 0.910 AUC on Orange and Cell2Cell telecom datasets, respectively. 7) Extracting 47 useful features from 260 original features of Orange dataset and 35 features from 76 original features of Cell2Cell dataset. In short, under this research work extensive simulations are performed to examine the prediction performance of the proposed churn prediction systems distinguishing churners from non-churners.