It is an active topic to investigate the schemes based on machine learning (ML) methods for detecting pulsars as the data volume growing exponentially in modern surveys. To improve the detection performance, input features into an ML model should be investigated specifically. In the existing pulsar detection researches based on ML methods, there are mainly two kinds of feature designs: the empirical features and statistical features. Due to the combinational effects from multiple features, however, there exist some redundancies and even irrelevant components in the available features, which can reduce the accuracy of a pulsar detection model. Therefore, it is essential to select a subset of relevant features from a set of available candidate features and known as feature selection. In this work, two feature selection algorithms --Grid Search (GS) and Recursive Feature Elimination (RFE)--are proposed to improve the detection performance by removing the redundant and irrelevant features. The algorithms were evaluated on the Southern High Time Resolution University survey (HTRU-S) with five pulsar detection models. The experimental results verify the effectiveness and efficiency of our proposed feature selection algorithms. By the GS, a model with only two features reach a recall rate as high as 99% and a false positive rate (FPR) as low as 0.65%; By the RFE, another model with only three features achieves a recall rate 99% and an FPR of 0.16% in pulsar candidates classification. Furthermore, this work investigated the number of features required as well as the misclassified pulsars by our models.

We report the phase-connected timing ephemeris, polarization pulse profiles, Faraday rotation measurements, and Rotating-Vector-Model (RVM) fitting results of twelve millisecond pulsars (MSPs) discovered with the Five-hundred-meter Aperture Spherical radio Telescope (FAST) in the Commensal radio Astronomy FAST survey (CRAFTS). The timing campaigns were carried out with FAST and Arecibo over three years. Eleven of the twelve pulsars are in neutron star - white dwarf binary systems, with orbital periods between 2.4 and 100 d. Ten of them have spin periods, companion masses, and orbital eccentricities that are consistent with the theoretical expectations for MSP - Helium white dwarf (He WD) systems. The last binary pulsar (PSR J1912−0952) has a significantly smaller spin frequency and a smaller companion mass, the latter could be caused by a low orbital inclination for the system. Its orbital period of 29 days is well within the range of orbital periods where some MSP - He WD systems have shown anomalous eccentricities, however, the eccentricity of PSR J1912−0952 is typical of what one finds for the remaining MSP - He WD systems.